linux_dsm_epyc7002/tools/perf/bench/numa.c

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License cleanup: add SPDX GPL-2.0 license identifier to files with no license Many source files in the tree are missing licensing information, which makes it harder for compliance tools to determine the correct license. By default all files without license information are under the default license of the kernel, which is GPL version 2. Update the files which contain no license information with the 'GPL-2.0' SPDX license identifier. The SPDX identifier is a legally binding shorthand, which can be used instead of the full boiler plate text. This patch is based on work done by Thomas Gleixner and Kate Stewart and Philippe Ombredanne. How this work was done: Patches were generated and checked against linux-4.14-rc6 for a subset of the use cases: - file had no licensing information it it. - file was a */uapi/* one with no licensing information in it, - file was a */uapi/* one with existing licensing information, Further patches will be generated in subsequent months to fix up cases where non-standard license headers were used, and references to license had to be inferred by heuristics based on keywords. The analysis to determine which SPDX License Identifier to be applied to a file was done in a spreadsheet of side by side results from of the output of two independent scanners (ScanCode & Windriver) producing SPDX tag:value files created by Philippe Ombredanne. Philippe prepared the base worksheet, and did an initial spot review of a few 1000 files. The 4.13 kernel was the starting point of the analysis with 60,537 files assessed. Kate Stewart did a file by file comparison of the scanner results in the spreadsheet to determine which SPDX license identifier(s) to be applied to the file. She confirmed any determination that was not immediately clear with lawyers working with the Linux Foundation. Criteria used to select files for SPDX license identifier tagging was: - Files considered eligible had to be source code files. - Make and config files were included as candidates if they contained >5 lines of source - File already had some variant of a license header in it (even if <5 lines). All documentation files were explicitly excluded. The following heuristics were used to determine which SPDX license identifiers to apply. - when both scanners couldn't find any license traces, file was considered to have no license information in it, and the top level COPYING file license applied. For non */uapi/* files that summary was: SPDX license identifier # files ---------------------------------------------------|------- GPL-2.0 11139 and resulted in the first patch in this series. If that file was a */uapi/* path one, it was "GPL-2.0 WITH Linux-syscall-note" otherwise it was "GPL-2.0". Results of that was: SPDX license identifier # files ---------------------------------------------------|------- GPL-2.0 WITH Linux-syscall-note 930 and resulted in the second patch in this series. - if a file had some form of licensing information in it, and was one of the */uapi/* ones, it was denoted with the Linux-syscall-note if any GPL family license was found in the file or had no licensing in it (per prior point). Results summary: SPDX license identifier # files ---------------------------------------------------|------ GPL-2.0 WITH Linux-syscall-note 270 GPL-2.0+ WITH Linux-syscall-note 169 ((GPL-2.0 WITH Linux-syscall-note) OR BSD-2-Clause) 21 ((GPL-2.0 WITH Linux-syscall-note) OR BSD-3-Clause) 17 LGPL-2.1+ WITH Linux-syscall-note 15 GPL-1.0+ WITH Linux-syscall-note 14 ((GPL-2.0+ WITH Linux-syscall-note) OR BSD-3-Clause) 5 LGPL-2.0+ WITH Linux-syscall-note 4 LGPL-2.1 WITH Linux-syscall-note 3 ((GPL-2.0 WITH Linux-syscall-note) OR MIT) 3 ((GPL-2.0 WITH Linux-syscall-note) AND MIT) 1 and that resulted in the third patch in this series. - when the two scanners agreed on the detected license(s), that became the concluded license(s). - when there was disagreement between the two scanners (one detected a license but the other didn't, or they both detected different licenses) a manual inspection of the file occurred. - In most cases a manual inspection of the information in the file resulted in a clear resolution of the license that should apply (and which scanner probably needed to revisit its heuristics). - When it was not immediately clear, the license identifier was confirmed with lawyers working with the Linux Foundation. - If there was any question as to the appropriate license identifier, the file was flagged for further research and to be revisited later in time. In total, over 70 hours of logged manual review was done on the spreadsheet to determine the SPDX license identifiers to apply to the source files by Kate, Philippe, Thomas and, in some cases, confirmation by lawyers working with the Linux Foundation. Kate also obtained a third independent scan of the 4.13 code base from FOSSology, and compared selected files where the other two scanners disagreed against that SPDX file, to see if there was new insights. The Windriver scanner is based on an older version of FOSSology in part, so they are related. Thomas did random spot checks in about 500 files from the spreadsheets for the uapi headers and agreed with SPDX license identifier in the files he inspected. For the non-uapi files Thomas did random spot checks in about 15000 files. In initial set of patches against 4.14-rc6, 3 files were found to have copy/paste license identifier errors, and have been fixed to reflect the correct identifier. Additionally Philippe spent 10 hours this week doing a detailed manual inspection and review of the 12,461 patched files from the initial patch version early this week with: - a full scancode scan run, collecting the matched texts, detected license ids and scores - reviewing anything where there was a license detected (about 500+ files) to ensure that the applied SPDX license was correct - reviewing anything where there was no detection but the patch license was not GPL-2.0 WITH Linux-syscall-note to ensure that the applied SPDX license was correct This produced a worksheet with 20 files needing minor correction. This worksheet was then exported into 3 different .csv files for the different types of files to be modified. These .csv files were then reviewed by Greg. Thomas wrote a script to parse the csv files and add the proper SPDX tag to the file, in the format that the file expected. This script was further refined by Greg based on the output to detect more types of files automatically and to distinguish between header and source .c files (which need different comment types.) Finally Greg ran the script using the .csv files to generate the patches. Reviewed-by: Kate Stewart <kstewart@linuxfoundation.org> Reviewed-by: Philippe Ombredanne <pombredanne@nexb.com> Reviewed-by: Thomas Gleixner <tglx@linutronix.de> Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>
2017-11-01 21:07:57 +07:00
// SPDX-License-Identifier: GPL-2.0
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
/*
* numa.c
*
* numa: Simulate NUMA-sensitive workload and measure their NUMA performance
*/
#include <inttypes.h>
/* For the CLR_() macros */
#include <pthread.h>
#include <subcmd/parse-options.h>
#include "../util/cloexec.h"
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
#include "bench.h"
#include <errno.h>
#include <sched.h>
#include <stdio.h>
#include <assert.h>
#include <malloc.h>
#include <signal.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include <sys/mman.h>
#include <sys/time.h>
#include <sys/resource.h>
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
#include <sys/wait.h>
#include <sys/prctl.h>
#include <sys/types.h>
#include <linux/kernel.h>
#include <linux/time64.h>
#include <linux/numa.h>
#include <linux/zalloc.h>
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
#include <numa.h>
#include <numaif.h>
perf bench numa: Add define for RUSAGE_THREAD if not present While cross building perf to the ARC architecture on a fedora 30 host, we were failing with: CC /tmp/build/perf/bench/numa.o bench/numa.c: In function ‘worker_thread’: bench/numa.c:1261:12: error: ‘RUSAGE_THREAD’ undeclared (first use in this function); did you mean ‘SIGEV_THREAD’? getrusage(RUSAGE_THREAD, &rusage); ^~~~~~~~~~~~~ SIGEV_THREAD bench/numa.c:1261:12: note: each undeclared identifier is reported only once for each function it appears in [perfbuilder@60d5802468f6 perf]$ /arc_gnu_2019.03-rc1_prebuilt_uclibc_le_archs_linux_install/bin/arc-linux-gcc --version | head -1 arc-linux-gcc (ARCv2 ISA Linux uClibc toolchain 2019.03-rc1) 8.3.1 20190225 [perfbuilder@60d5802468f6 perf]$ Trying to reproduce a report by Vineet, I noticed that, with just cross-built zlib and numactl libraries, I ended up with the above failure. So, since RUSAGE_THREAD is available as a define, check for that and numactl libraries, I ended up with the above failure. So, since RUSAGE_THREAD is available as a define in the system headers, check if it is defined in the 'perf bench numa' sources and define it if not. Now it builds and I have to figure out if the problem reported by Vineet only takes place if we have libelf or some other library available. Cc: Arnd Bergmann <arnd@arndb.de> Cc: Jiri Olsa <jolsa@kernel.org> Cc: linux-snps-arc@lists.infradead.org Cc: Namhyung Kim <namhyung@kernel.org> Cc: Vineet Gupta <Vineet.Gupta1@synopsys.com> Link: https://lkml.kernel.org/n/tip-2wb4r1gir9xrevbpq7qp0amk@git.kernel.org Signed-off-by: Arnaldo Carvalho de Melo <acme@redhat.com>
2019-04-26 04:36:51 +07:00
#ifndef RUSAGE_THREAD
# define RUSAGE_THREAD 1
#endif
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
/*
* Regular printout to the terminal, supressed if -q is specified:
*/
#define tprintf(x...) do { if (g && g->p.show_details >= 0) printf(x); } while (0)
/*
* Debug printf:
*/
#undef dprintf
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
#define dprintf(x...) do { if (g && g->p.show_details >= 1) printf(x); } while (0)
struct thread_data {
int curr_cpu;
cpu_set_t bind_cpumask;
int bind_node;
u8 *process_data;
int process_nr;
int thread_nr;
int task_nr;
unsigned int loops_done;
u64 val;
u64 runtime_ns;
u64 system_time_ns;
u64 user_time_ns;
double speed_gbs;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
pthread_mutex_t *process_lock;
};
/* Parameters set by options: */
struct params {
/* Startup synchronization: */
bool serialize_startup;
/* Task hierarchy: */
int nr_proc;
int nr_threads;
/* Working set sizes: */
const char *mb_global_str;
const char *mb_proc_str;
const char *mb_proc_locked_str;
const char *mb_thread_str;
double mb_global;
double mb_proc;
double mb_proc_locked;
double mb_thread;
/* Access patterns to the working set: */
bool data_reads;
bool data_writes;
bool data_backwards;
bool data_zero_memset;
bool data_rand_walk;
u32 nr_loops;
u32 nr_secs;
u32 sleep_usecs;
/* Working set initialization: */
bool init_zero;
bool init_random;
bool init_cpu0;
/* Misc options: */
int show_details;
int run_all;
int thp;
long bytes_global;
long bytes_process;
long bytes_process_locked;
long bytes_thread;
int nr_tasks;
bool show_quiet;
bool show_convergence;
bool measure_convergence;
int perturb_secs;
int nr_cpus;
int nr_nodes;
/* Affinity options -C and -N: */
char *cpu_list_str;
char *node_list_str;
};
/* Global, read-writable area, accessible to all processes and threads: */
struct global_info {
u8 *data;
pthread_mutex_t startup_mutex;
int nr_tasks_started;
pthread_mutex_t startup_done_mutex;
pthread_mutex_t start_work_mutex;
int nr_tasks_working;
pthread_mutex_t stop_work_mutex;
u64 bytes_done;
struct thread_data *threads;
/* Convergence latency measurement: */
bool all_converged;
bool stop_work;
int print_once;
struct params p;
};
static struct global_info *g = NULL;
static int parse_cpus_opt(const struct option *opt, const char *arg, int unset);
static int parse_nodes_opt(const struct option *opt, const char *arg, int unset);
struct params p0;
static const struct option options[] = {
OPT_INTEGER('p', "nr_proc" , &p0.nr_proc, "number of processes"),
OPT_INTEGER('t', "nr_threads" , &p0.nr_threads, "number of threads per process"),
OPT_STRING('G', "mb_global" , &p0.mb_global_str, "MB", "global memory (MBs)"),
OPT_STRING('P', "mb_proc" , &p0.mb_proc_str, "MB", "process memory (MBs)"),
OPT_STRING('L', "mb_proc_locked", &p0.mb_proc_locked_str,"MB", "process serialized/locked memory access (MBs), <= process_memory"),
OPT_STRING('T', "mb_thread" , &p0.mb_thread_str, "MB", "thread memory (MBs)"),
OPT_UINTEGER('l', "nr_loops" , &p0.nr_loops, "max number of loops to run (default: unlimited)"),
OPT_UINTEGER('s', "nr_secs" , &p0.nr_secs, "max number of seconds to run (default: 5 secs)"),
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
OPT_UINTEGER('u', "usleep" , &p0.sleep_usecs, "usecs to sleep per loop iteration"),
OPT_BOOLEAN('R', "data_reads" , &p0.data_reads, "access the data via reads (can be mixed with -W)"),
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
OPT_BOOLEAN('W', "data_writes" , &p0.data_writes, "access the data via writes (can be mixed with -R)"),
OPT_BOOLEAN('B', "data_backwards", &p0.data_backwards, "access the data backwards as well"),
OPT_BOOLEAN('Z', "data_zero_memset", &p0.data_zero_memset,"access the data via glibc bzero only"),
OPT_BOOLEAN('r', "data_rand_walk", &p0.data_rand_walk, "access the data with random (32bit LFSR) walk"),
OPT_BOOLEAN('z', "init_zero" , &p0.init_zero, "bzero the initial allocations"),
OPT_BOOLEAN('I', "init_random" , &p0.init_random, "randomize the contents of the initial allocations"),
OPT_BOOLEAN('0', "init_cpu0" , &p0.init_cpu0, "do the initial allocations on CPU#0"),
OPT_INTEGER('x', "perturb_secs", &p0.perturb_secs, "perturb thread 0/0 every X secs, to test convergence stability"),
OPT_INCR ('d', "show_details" , &p0.show_details, "Show details"),
OPT_INCR ('a', "all" , &p0.run_all, "Run all tests in the suite"),
OPT_INTEGER('H', "thp" , &p0.thp, "MADV_NOHUGEPAGE < 0 < MADV_HUGEPAGE"),
OPT_BOOLEAN('c', "show_convergence", &p0.show_convergence, "show convergence details, "
"convergence is reached when each process (all its threads) is running on a single NUMA node."),
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
OPT_BOOLEAN('m', "measure_convergence", &p0.measure_convergence, "measure convergence latency"),
OPT_BOOLEAN('q', "quiet" , &p0.show_quiet, "quiet mode"),
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
OPT_BOOLEAN('S', "serialize-startup", &p0.serialize_startup,"serialize thread startup"),
/* Special option string parsing callbacks: */
OPT_CALLBACK('C', "cpus", NULL, "cpu[,cpu2,...cpuN]",
"bind the first N tasks to these specific cpus (the rest is unbound)",
parse_cpus_opt),
OPT_CALLBACK('M', "memnodes", NULL, "node[,node2,...nodeN]",
"bind the first N tasks to these specific memory nodes (the rest is unbound)",
parse_nodes_opt),
OPT_END()
};
static const char * const bench_numa_usage[] = {
"perf bench numa <options>",
NULL
};
static const char * const numa_usage[] = {
"perf bench numa mem [<options>]",
NULL
};
/*
* To get number of numa nodes present.
*/
static int nr_numa_nodes(void)
{
int i, nr_nodes = 0;
for (i = 0; i < g->p.nr_nodes; i++) {
if (numa_bitmask_isbitset(numa_nodes_ptr, i))
nr_nodes++;
}
return nr_nodes;
}
/*
* To check if given numa node is present.
*/
static int is_node_present(int node)
{
return numa_bitmask_isbitset(numa_nodes_ptr, node);
}
/*
* To check given numa node has cpus.
*/
static bool node_has_cpus(int node)
{
struct bitmask *cpu = numa_allocate_cpumask();
unsigned int i;
if (cpu && !numa_node_to_cpus(node, cpu)) {
for (i = 0; i < cpu->size; i++) {
if (numa_bitmask_isbitset(cpu, i))
return true;
}
}
return false; /* lets fall back to nocpus safely */
}
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
static cpu_set_t bind_to_cpu(int target_cpu)
{
cpu_set_t orig_mask, mask;
int ret;
ret = sched_getaffinity(0, sizeof(orig_mask), &orig_mask);
BUG_ON(ret);
CPU_ZERO(&mask);
if (target_cpu == -1) {
int cpu;
for (cpu = 0; cpu < g->p.nr_cpus; cpu++)
CPU_SET(cpu, &mask);
} else {
BUG_ON(target_cpu < 0 || target_cpu >= g->p.nr_cpus);
CPU_SET(target_cpu, &mask);
}
ret = sched_setaffinity(0, sizeof(mask), &mask);
BUG_ON(ret);
return orig_mask;
}
static cpu_set_t bind_to_node(int target_node)
{
int cpus_per_node = g->p.nr_cpus / nr_numa_nodes();
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
cpu_set_t orig_mask, mask;
int cpu;
int ret;
BUG_ON(cpus_per_node * nr_numa_nodes() != g->p.nr_cpus);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
BUG_ON(!cpus_per_node);
ret = sched_getaffinity(0, sizeof(orig_mask), &orig_mask);
BUG_ON(ret);
CPU_ZERO(&mask);
if (target_node == NUMA_NO_NODE) {
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
for (cpu = 0; cpu < g->p.nr_cpus; cpu++)
CPU_SET(cpu, &mask);
} else {
int cpu_start = (target_node + 0) * cpus_per_node;
int cpu_stop = (target_node + 1) * cpus_per_node;
BUG_ON(cpu_stop > g->p.nr_cpus);
for (cpu = cpu_start; cpu < cpu_stop; cpu++)
CPU_SET(cpu, &mask);
}
ret = sched_setaffinity(0, sizeof(mask), &mask);
BUG_ON(ret);
return orig_mask;
}
static void bind_to_cpumask(cpu_set_t mask)
{
int ret;
ret = sched_setaffinity(0, sizeof(mask), &mask);
BUG_ON(ret);
}
static void mempol_restore(void)
{
int ret;
ret = set_mempolicy(MPOL_DEFAULT, NULL, g->p.nr_nodes-1);
BUG_ON(ret);
}
static void bind_to_memnode(int node)
{
unsigned long nodemask;
int ret;
if (node == NUMA_NO_NODE)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
return;
BUG_ON(g->p.nr_nodes > (int)sizeof(nodemask)*8);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
nodemask = 1L << node;
ret = set_mempolicy(MPOL_BIND, &nodemask, sizeof(nodemask)*8);
dprintf("binding to node %d, mask: %016lx => %d\n", node, nodemask, ret);
BUG_ON(ret);
}
#define HPSIZE (2*1024*1024)
#define set_taskname(fmt...) \
do { \
char name[20]; \
\
snprintf(name, 20, fmt); \
prctl(PR_SET_NAME, name); \
} while (0)
static u8 *alloc_data(ssize_t bytes0, int map_flags,
int init_zero, int init_cpu0, int thp, int init_random)
{
cpu_set_t orig_mask;
ssize_t bytes;
u8 *buf;
int ret;
if (!bytes0)
return NULL;
/* Allocate and initialize all memory on CPU#0: */
if (init_cpu0) {
int node = numa_node_of_cpu(0);
orig_mask = bind_to_node(node);
bind_to_memnode(node);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
}
bytes = bytes0 + HPSIZE;
buf = (void *)mmap(0, bytes, PROT_READ|PROT_WRITE, MAP_ANON|map_flags, -1, 0);
BUG_ON(buf == (void *)-1);
if (map_flags == MAP_PRIVATE) {
if (thp > 0) {
ret = madvise(buf, bytes, MADV_HUGEPAGE);
if (ret && !g->print_once) {
g->print_once = 1;
printf("WARNING: Could not enable THP - do: 'echo madvise > /sys/kernel/mm/transparent_hugepage/enabled'\n");
}
}
if (thp < 0) {
ret = madvise(buf, bytes, MADV_NOHUGEPAGE);
if (ret && !g->print_once) {
g->print_once = 1;
printf("WARNING: Could not disable THP: run a CONFIG_TRANSPARENT_HUGEPAGE kernel?\n");
}
}
}
if (init_zero) {
bzero(buf, bytes);
} else {
/* Initialize random contents, different in each word: */
if (init_random) {
u64 *wbuf = (void *)buf;
long off = rand();
long i;
for (i = 0; i < bytes/8; i++)
wbuf[i] = i + off;
}
}
/* Align to 2MB boundary: */
buf = (void *)(((unsigned long)buf + HPSIZE-1) & ~(HPSIZE-1));
/* Restore affinity: */
if (init_cpu0) {
bind_to_cpumask(orig_mask);
mempol_restore();
}
return buf;
}
static void free_data(void *data, ssize_t bytes)
{
int ret;
if (!data)
return;
ret = munmap(data, bytes);
BUG_ON(ret);
}
/*
* Create a shared memory buffer that can be shared between processes, zeroed:
*/
static void * zalloc_shared_data(ssize_t bytes)
{
return alloc_data(bytes, MAP_SHARED, 1, g->p.init_cpu0, g->p.thp, g->p.init_random);
}
/*
* Create a shared memory buffer that can be shared between processes:
*/
static void * setup_shared_data(ssize_t bytes)
{
return alloc_data(bytes, MAP_SHARED, 0, g->p.init_cpu0, g->p.thp, g->p.init_random);
}
/*
* Allocate process-local memory - this will either be shared between
* threads of this process, or only be accessed by this thread:
*/
static void * setup_private_data(ssize_t bytes)
{
return alloc_data(bytes, MAP_PRIVATE, 0, g->p.init_cpu0, g->p.thp, g->p.init_random);
}
/*
* Return a process-shared (global) mutex:
*/
static void init_global_mutex(pthread_mutex_t *mutex)
{
pthread_mutexattr_t attr;
pthread_mutexattr_init(&attr);
pthread_mutexattr_setpshared(&attr, PTHREAD_PROCESS_SHARED);
pthread_mutex_init(mutex, &attr);
}
static int parse_cpu_list(const char *arg)
{
p0.cpu_list_str = strdup(arg);
dprintf("got CPU list: {%s}\n", p0.cpu_list_str);
return 0;
}
static int parse_setup_cpu_list(void)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
{
struct thread_data *td;
char *str0, *str;
int t;
if (!g->p.cpu_list_str)
return 0;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
dprintf("g->p.nr_tasks: %d\n", g->p.nr_tasks);
str0 = str = strdup(g->p.cpu_list_str);
t = 0;
BUG_ON(!str);
tprintf("# binding tasks to CPUs:\n");
tprintf("# ");
while (true) {
int bind_cpu, bind_cpu_0, bind_cpu_1;
char *tok, *tok_end, *tok_step, *tok_len, *tok_mul;
int bind_len;
int step;
int mul;
tok = strsep(&str, ",");
if (!tok)
break;
tok_end = strstr(tok, "-");
dprintf("\ntoken: {%s}, end: {%s}\n", tok, tok_end);
if (!tok_end) {
/* Single CPU specified: */
bind_cpu_0 = bind_cpu_1 = atol(tok);
} else {
/* CPU range specified (for example: "5-11"): */
bind_cpu_0 = atol(tok);
bind_cpu_1 = atol(tok_end + 1);
}
step = 1;
tok_step = strstr(tok, "#");
if (tok_step) {
step = atol(tok_step + 1);
BUG_ON(step <= 0 || step >= g->p.nr_cpus);
}
/*
* Mask length.
* Eg: "--cpus 8_4-16#4" means: '--cpus 8_4,12_4,16_4',
* where the _4 means the next 4 CPUs are allowed.
*/
bind_len = 1;
tok_len = strstr(tok, "_");
if (tok_len) {
bind_len = atol(tok_len + 1);
BUG_ON(bind_len <= 0 || bind_len > g->p.nr_cpus);
}
/* Multiplicator shortcut, "0x8" is a shortcut for: "0,0,0,0,0,0,0,0" */
mul = 1;
tok_mul = strstr(tok, "x");
if (tok_mul) {
mul = atol(tok_mul + 1);
BUG_ON(mul <= 0);
}
dprintf("CPUs: %d_%d-%d#%dx%d\n", bind_cpu_0, bind_len, bind_cpu_1, step, mul);
if (bind_cpu_0 >= g->p.nr_cpus || bind_cpu_1 >= g->p.nr_cpus) {
printf("\nTest not applicable, system has only %d CPUs.\n", g->p.nr_cpus);
return -1;
}
BUG_ON(bind_cpu_0 < 0 || bind_cpu_1 < 0);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
BUG_ON(bind_cpu_0 > bind_cpu_1);
for (bind_cpu = bind_cpu_0; bind_cpu <= bind_cpu_1; bind_cpu += step) {
int i;
for (i = 0; i < mul; i++) {
int cpu;
if (t >= g->p.nr_tasks) {
printf("\n# NOTE: ignoring bind CPUs starting at CPU#%d\n #", bind_cpu);
goto out;
}
td = g->threads + t;
if (t)
tprintf(",");
if (bind_len > 1) {
tprintf("%2d/%d", bind_cpu, bind_len);
} else {
tprintf("%2d", bind_cpu);
}
CPU_ZERO(&td->bind_cpumask);
for (cpu = bind_cpu; cpu < bind_cpu+bind_len; cpu++) {
BUG_ON(cpu < 0 || cpu >= g->p.nr_cpus);
CPU_SET(cpu, &td->bind_cpumask);
}
t++;
}
}
}
out:
tprintf("\n");
if (t < g->p.nr_tasks)
printf("# NOTE: %d tasks bound, %d tasks unbound\n", t, g->p.nr_tasks - t);
free(str0);
return 0;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
}
static int parse_cpus_opt(const struct option *opt __maybe_unused,
const char *arg, int unset __maybe_unused)
{
if (!arg)
return -1;
return parse_cpu_list(arg);
}
static int parse_node_list(const char *arg)
{
p0.node_list_str = strdup(arg);
dprintf("got NODE list: {%s}\n", p0.node_list_str);
return 0;
}
static int parse_setup_node_list(void)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
{
struct thread_data *td;
char *str0, *str;
int t;
if (!g->p.node_list_str)
return 0;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
dprintf("g->p.nr_tasks: %d\n", g->p.nr_tasks);
str0 = str = strdup(g->p.node_list_str);
t = 0;
BUG_ON(!str);
tprintf("# binding tasks to NODEs:\n");
tprintf("# ");
while (true) {
int bind_node, bind_node_0, bind_node_1;
char *tok, *tok_end, *tok_step, *tok_mul;
int step;
int mul;
tok = strsep(&str, ",");
if (!tok)
break;
tok_end = strstr(tok, "-");
dprintf("\ntoken: {%s}, end: {%s}\n", tok, tok_end);
if (!tok_end) {
/* Single NODE specified: */
bind_node_0 = bind_node_1 = atol(tok);
} else {
/* NODE range specified (for example: "5-11"): */
bind_node_0 = atol(tok);
bind_node_1 = atol(tok_end + 1);
}
step = 1;
tok_step = strstr(tok, "#");
if (tok_step) {
step = atol(tok_step + 1);
BUG_ON(step <= 0 || step >= g->p.nr_nodes);
}
/* Multiplicator shortcut, "0x8" is a shortcut for: "0,0,0,0,0,0,0,0" */
mul = 1;
tok_mul = strstr(tok, "x");
if (tok_mul) {
mul = atol(tok_mul + 1);
BUG_ON(mul <= 0);
}
dprintf("NODEs: %d-%d #%d\n", bind_node_0, bind_node_1, step);
if (bind_node_0 >= g->p.nr_nodes || bind_node_1 >= g->p.nr_nodes) {
printf("\nTest not applicable, system has only %d nodes.\n", g->p.nr_nodes);
return -1;
}
BUG_ON(bind_node_0 < 0 || bind_node_1 < 0);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
BUG_ON(bind_node_0 > bind_node_1);
for (bind_node = bind_node_0; bind_node <= bind_node_1; bind_node += step) {
int i;
for (i = 0; i < mul; i++) {
if (t >= g->p.nr_tasks || !node_has_cpus(bind_node)) {
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
printf("\n# NOTE: ignoring bind NODEs starting at NODE#%d\n", bind_node);
goto out;
}
td = g->threads + t;
if (!t)
tprintf(" %2d", bind_node);
else
tprintf(",%2d", bind_node);
td->bind_node = bind_node;
t++;
}
}
}
out:
tprintf("\n");
if (t < g->p.nr_tasks)
printf("# NOTE: %d tasks mem-bound, %d tasks unbound\n", t, g->p.nr_tasks - t);
free(str0);
return 0;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
}
static int parse_nodes_opt(const struct option *opt __maybe_unused,
const char *arg, int unset __maybe_unused)
{
if (!arg)
return -1;
return parse_node_list(arg);
return 0;
}
#define BIT(x) (1ul << x)
static inline uint32_t lfsr_32(uint32_t lfsr)
{
const uint32_t taps = BIT(1) | BIT(5) | BIT(6) | BIT(31);
return (lfsr>>1) ^ ((0x0u - (lfsr & 0x1u)) & taps);
}
/*
* Make sure there's real data dependency to RAM (when read
* accesses are enabled), so the compiler, the CPU and the
* kernel (KSM, zero page, etc.) cannot optimize away RAM
* accesses:
*/
static inline u64 access_data(u64 *data, u64 val)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
{
if (g->p.data_reads)
val += *data;
if (g->p.data_writes)
*data = val + 1;
return val;
}
/*
* The worker process does two types of work, a forwards going
* loop and a backwards going loop.
*
* We do this so that on multiprocessor systems we do not create
* a 'train' of processing, with highly synchronized processes,
* skewing the whole benchmark.
*/
static u64 do_work(u8 *__data, long bytes, int nr, int nr_max, int loop, u64 val)
{
long words = bytes/sizeof(u64);
u64 *data = (void *)__data;
long chunk_0, chunk_1;
u64 *d0, *d, *d1;
long off;
long i;
BUG_ON(!data && words);
BUG_ON(data && !words);
if (!data)
return val;
/* Very simple memset() work variant: */
if (g->p.data_zero_memset && !g->p.data_rand_walk) {
bzero(data, bytes);
return val;
}
/* Spread out by PID/TID nr and by loop nr: */
chunk_0 = words/nr_max;
chunk_1 = words/g->p.nr_loops;
off = nr*chunk_0 + loop*chunk_1;
while (off >= words)
off -= words;
if (g->p.data_rand_walk) {
u32 lfsr = nr + loop + val;
int j;
for (i = 0; i < words/1024; i++) {
long start, end;
lfsr = lfsr_32(lfsr);
start = lfsr % words;
end = min(start + 1024, words-1);
if (g->p.data_zero_memset) {
bzero(data + start, (end-start) * sizeof(u64));
} else {
for (j = start; j < end; j++)
val = access_data(data + j, val);
}
}
} else if (!g->p.data_backwards || (nr + loop) & 1) {
d0 = data + off;
d = data + off + 1;
d1 = data + words;
/* Process data forwards: */
for (;;) {
if (unlikely(d >= d1))
d = data;
if (unlikely(d == d0))
break;
val = access_data(d, val);
d++;
}
} else {
/* Process data backwards: */
d0 = data + off;
d = data + off - 1;
d1 = data + words;
/* Process data forwards: */
for (;;) {
if (unlikely(d < data))
d = data + words-1;
if (unlikely(d == d0))
break;
val = access_data(d, val);
d--;
}
}
return val;
}
static void update_curr_cpu(int task_nr, unsigned long bytes_worked)
{
unsigned int cpu;
cpu = sched_getcpu();
g->threads[task_nr].curr_cpu = cpu;
prctl(0, bytes_worked);
}
#define MAX_NR_NODES 64
/*
* Count the number of nodes a process's threads
* are spread out on.
*
* A count of 1 means that the process is compressed
* to a single node. A count of g->p.nr_nodes means it's
* spread out on the whole system.
*/
static int count_process_nodes(int process_nr)
{
char node_present[MAX_NR_NODES] = { 0, };
int nodes;
int n, t;
for (t = 0; t < g->p.nr_threads; t++) {
struct thread_data *td;
int task_nr;
int node;
task_nr = process_nr*g->p.nr_threads + t;
td = g->threads + task_nr;
node = numa_node_of_cpu(td->curr_cpu);
if (node < 0) /* curr_cpu was likely still -1 */
return 0;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
node_present[node] = 1;
}
nodes = 0;
for (n = 0; n < MAX_NR_NODES; n++)
nodes += node_present[n];
return nodes;
}
/*
* Count the number of distinct process-threads a node contains.
*
* A count of 1 means that the node contains only a single
* process. If all nodes on the system contain at most one
* process then we are well-converged.
*/
static int count_node_processes(int node)
{
int processes = 0;
int t, p;
for (p = 0; p < g->p.nr_proc; p++) {
for (t = 0; t < g->p.nr_threads; t++) {
struct thread_data *td;
int task_nr;
int n;
task_nr = p*g->p.nr_threads + t;
td = g->threads + task_nr;
n = numa_node_of_cpu(td->curr_cpu);
if (n == node) {
processes++;
break;
}
}
}
return processes;
}
static void calc_convergence_compression(int *strong)
{
unsigned int nodes_min, nodes_max;
int p;
nodes_min = -1;
nodes_max = 0;
for (p = 0; p < g->p.nr_proc; p++) {
unsigned int nodes = count_process_nodes(p);
if (!nodes) {
*strong = 0;
return;
}
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
nodes_min = min(nodes, nodes_min);
nodes_max = max(nodes, nodes_max);
}
/* Strong convergence: all threads compress on a single node: */
if (nodes_min == 1 && nodes_max == 1) {
*strong = 1;
} else {
*strong = 0;
tprintf(" {%d-%d}", nodes_min, nodes_max);
}
}
static void calc_convergence(double runtime_ns_max, double *convergence)
{
unsigned int loops_done_min, loops_done_max;
int process_groups;
int nodes[MAX_NR_NODES];
int distance;
int nr_min;
int nr_max;
int strong;
int sum;
int nr;
int node;
int cpu;
int t;
if (!g->p.show_convergence && !g->p.measure_convergence)
return;
for (node = 0; node < g->p.nr_nodes; node++)
nodes[node] = 0;
loops_done_min = -1;
loops_done_max = 0;
for (t = 0; t < g->p.nr_tasks; t++) {
struct thread_data *td = g->threads + t;
unsigned int loops_done;
cpu = td->curr_cpu;
/* Not all threads have written it yet: */
if (cpu < 0)
continue;
node = numa_node_of_cpu(cpu);
nodes[node]++;
loops_done = td->loops_done;
loops_done_min = min(loops_done, loops_done_min);
loops_done_max = max(loops_done, loops_done_max);
}
nr_max = 0;
nr_min = g->p.nr_tasks;
sum = 0;
for (node = 0; node < g->p.nr_nodes; node++) {
if (!is_node_present(node))
continue;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
nr = nodes[node];
nr_min = min(nr, nr_min);
nr_max = max(nr, nr_max);
sum += nr;
}
BUG_ON(nr_min > nr_max);
BUG_ON(sum > g->p.nr_tasks);
if (0 && (sum < g->p.nr_tasks))
return;
/*
* Count the number of distinct process groups present
* on nodes - when we are converged this will decrease
* to g->p.nr_proc:
*/
process_groups = 0;
for (node = 0; node < g->p.nr_nodes; node++) {
int processes;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
if (!is_node_present(node))
continue;
processes = count_node_processes(node);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
nr = nodes[node];
tprintf(" %2d/%-2d", nr, processes);
process_groups += processes;
}
distance = nr_max - nr_min;
tprintf(" [%2d/%-2d]", distance, process_groups);
tprintf(" l:%3d-%-3d (%3d)",
loops_done_min, loops_done_max, loops_done_max-loops_done_min);
if (loops_done_min && loops_done_max) {
double skew = 1.0 - (double)loops_done_min/loops_done_max;
tprintf(" [%4.1f%%]", skew * 100.0);
}
calc_convergence_compression(&strong);
if (strong && process_groups == g->p.nr_proc) {
if (!*convergence) {
*convergence = runtime_ns_max;
tprintf(" (%6.1fs converged)\n", *convergence / NSEC_PER_SEC);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
if (g->p.measure_convergence) {
g->all_converged = true;
g->stop_work = true;
}
}
} else {
if (*convergence) {
tprintf(" (%6.1fs de-converged)", runtime_ns_max / NSEC_PER_SEC);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
*convergence = 0;
}
tprintf("\n");
}
}
static void show_summary(double runtime_ns_max, int l, double *convergence)
{
tprintf("\r # %5.1f%% [%.1f mins]",
(double)(l+1)/g->p.nr_loops*100.0, runtime_ns_max / NSEC_PER_SEC / 60.0);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
calc_convergence(runtime_ns_max, convergence);
if (g->p.show_details >= 0)
fflush(stdout);
}
static void *worker_thread(void *__tdata)
{
struct thread_data *td = __tdata;
struct timeval start0, start, stop, diff;
int process_nr = td->process_nr;
int thread_nr = td->thread_nr;
unsigned long last_perturbance;
int task_nr = td->task_nr;
int details = g->p.show_details;
int first_task, last_task;
double convergence = 0;
u64 val = td->val;
double runtime_ns_max;
u8 *global_data;
u8 *process_data;
u8 *thread_data;
u64 bytes_done, secs;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
long work_done;
u32 l;
struct rusage rusage;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
bind_to_cpumask(td->bind_cpumask);
bind_to_memnode(td->bind_node);
set_taskname("thread %d/%d", process_nr, thread_nr);
global_data = g->data;
process_data = td->process_data;
thread_data = setup_private_data(g->p.bytes_thread);
bytes_done = 0;
last_task = 0;
if (process_nr == g->p.nr_proc-1 && thread_nr == g->p.nr_threads-1)
last_task = 1;
first_task = 0;
if (process_nr == 0 && thread_nr == 0)
first_task = 1;
if (details >= 2) {
printf("# thread %2d / %2d global mem: %p, process mem: %p, thread mem: %p\n",
process_nr, thread_nr, global_data, process_data, thread_data);
}
if (g->p.serialize_startup) {
pthread_mutex_lock(&g->startup_mutex);
g->nr_tasks_started++;
pthread_mutex_unlock(&g->startup_mutex);
/* Here we will wait for the main process to start us all at once: */
pthread_mutex_lock(&g->start_work_mutex);
g->nr_tasks_working++;
/* Last one wake the main process: */
if (g->nr_tasks_working == g->p.nr_tasks)
pthread_mutex_unlock(&g->startup_done_mutex);
pthread_mutex_unlock(&g->start_work_mutex);
}
gettimeofday(&start0, NULL);
start = stop = start0;
last_perturbance = start.tv_sec;
for (l = 0; l < g->p.nr_loops; l++) {
start = stop;
if (g->stop_work)
break;
val += do_work(global_data, g->p.bytes_global, process_nr, g->p.nr_proc, l, val);
val += do_work(process_data, g->p.bytes_process, thread_nr, g->p.nr_threads, l, val);
val += do_work(thread_data, g->p.bytes_thread, 0, 1, l, val);
if (g->p.sleep_usecs) {
pthread_mutex_lock(td->process_lock);
usleep(g->p.sleep_usecs);
pthread_mutex_unlock(td->process_lock);
}
/*
* Amount of work to be done under a process-global lock:
*/
if (g->p.bytes_process_locked) {
pthread_mutex_lock(td->process_lock);
val += do_work(process_data, g->p.bytes_process_locked, thread_nr, g->p.nr_threads, l, val);
pthread_mutex_unlock(td->process_lock);
}
work_done = g->p.bytes_global + g->p.bytes_process +
g->p.bytes_process_locked + g->p.bytes_thread;
update_curr_cpu(task_nr, work_done);
bytes_done += work_done;
if (details < 0 && !g->p.perturb_secs && !g->p.measure_convergence && !g->p.nr_secs)
continue;
td->loops_done = l;
gettimeofday(&stop, NULL);
/* Check whether our max runtime timed out: */
if (g->p.nr_secs) {
timersub(&stop, &start0, &diff);
if ((u32)diff.tv_sec >= g->p.nr_secs) {
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
g->stop_work = true;
break;
}
}
/* Update the summary at most once per second: */
if (start.tv_sec == stop.tv_sec)
continue;
/*
* Perturb the first task's equilibrium every g->p.perturb_secs seconds,
* by migrating to CPU#0:
*/
if (first_task && g->p.perturb_secs && (int)(stop.tv_sec - last_perturbance) >= g->p.perturb_secs) {
cpu_set_t orig_mask;
int target_cpu;
int this_cpu;
last_perturbance = stop.tv_sec;
/*
* Depending on where we are running, move into
* the other half of the system, to create some
* real disturbance:
*/
this_cpu = g->threads[task_nr].curr_cpu;
if (this_cpu < g->p.nr_cpus/2)
target_cpu = g->p.nr_cpus-1;
else
target_cpu = 0;
orig_mask = bind_to_cpu(target_cpu);
/* Here we are running on the target CPU already */
if (details >= 1)
printf(" (injecting perturbalance, moved to CPU#%d)\n", target_cpu);
bind_to_cpumask(orig_mask);
}
if (details >= 3) {
timersub(&stop, &start, &diff);
runtime_ns_max = diff.tv_sec * NSEC_PER_SEC;
runtime_ns_max += diff.tv_usec * NSEC_PER_USEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
if (details >= 0) {
printf(" #%2d / %2d: %14.2lf nsecs/op [val: %016"PRIx64"]\n",
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
process_nr, thread_nr, runtime_ns_max / bytes_done, val);
}
fflush(stdout);
}
if (!last_task)
continue;
timersub(&stop, &start0, &diff);
runtime_ns_max = diff.tv_sec * NSEC_PER_SEC;
runtime_ns_max += diff.tv_usec * NSEC_PER_USEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
show_summary(runtime_ns_max, l, &convergence);
}
gettimeofday(&stop, NULL);
timersub(&stop, &start0, &diff);
td->runtime_ns = diff.tv_sec * NSEC_PER_SEC;
td->runtime_ns += diff.tv_usec * NSEC_PER_USEC;
secs = td->runtime_ns / NSEC_PER_SEC;
td->speed_gbs = secs ? bytes_done / secs / 1e9 : 0;
getrusage(RUSAGE_THREAD, &rusage);
td->system_time_ns = rusage.ru_stime.tv_sec * NSEC_PER_SEC;
td->system_time_ns += rusage.ru_stime.tv_usec * NSEC_PER_USEC;
td->user_time_ns = rusage.ru_utime.tv_sec * NSEC_PER_SEC;
td->user_time_ns += rusage.ru_utime.tv_usec * NSEC_PER_USEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
free_data(thread_data, g->p.bytes_thread);
pthread_mutex_lock(&g->stop_work_mutex);
g->bytes_done += bytes_done;
pthread_mutex_unlock(&g->stop_work_mutex);
return NULL;
}
/*
* A worker process starts a couple of threads:
*/
static void worker_process(int process_nr)
{
pthread_mutex_t process_lock;
struct thread_data *td;
pthread_t *pthreads;
u8 *process_data;
int task_nr;
int ret;
int t;
pthread_mutex_init(&process_lock, NULL);
set_taskname("process %d", process_nr);
/*
* Pick up the memory policy and the CPU binding of our first thread,
* so that we initialize memory accordingly:
*/
task_nr = process_nr*g->p.nr_threads;
td = g->threads + task_nr;
bind_to_memnode(td->bind_node);
bind_to_cpumask(td->bind_cpumask);
pthreads = zalloc(g->p.nr_threads * sizeof(pthread_t));
process_data = setup_private_data(g->p.bytes_process);
if (g->p.show_details >= 3) {
printf(" # process %2d global mem: %p, process mem: %p\n",
process_nr, g->data, process_data);
}
for (t = 0; t < g->p.nr_threads; t++) {
task_nr = process_nr*g->p.nr_threads + t;
td = g->threads + task_nr;
td->process_data = process_data;
td->process_nr = process_nr;
td->thread_nr = t;
td->task_nr = task_nr;
td->val = rand();
td->curr_cpu = -1;
td->process_lock = &process_lock;
ret = pthread_create(pthreads + t, NULL, worker_thread, td);
BUG_ON(ret);
}
for (t = 0; t < g->p.nr_threads; t++) {
ret = pthread_join(pthreads[t], NULL);
BUG_ON(ret);
}
free_data(process_data, g->p.bytes_process);
free(pthreads);
}
static void print_summary(void)
{
if (g->p.show_details < 0)
return;
printf("\n ###\n");
printf(" # %d %s will execute (on %d nodes, %d CPUs):\n",
g->p.nr_tasks, g->p.nr_tasks == 1 ? "task" : "tasks", nr_numa_nodes(), g->p.nr_cpus);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
printf(" # %5dx %5ldMB global shared mem operations\n",
g->p.nr_loops, g->p.bytes_global/1024/1024);
printf(" # %5dx %5ldMB process shared mem operations\n",
g->p.nr_loops, g->p.bytes_process/1024/1024);
printf(" # %5dx %5ldMB thread local mem operations\n",
g->p.nr_loops, g->p.bytes_thread/1024/1024);
printf(" ###\n");
printf("\n ###\n"); fflush(stdout);
}
static void init_thread_data(void)
{
ssize_t size = sizeof(*g->threads)*g->p.nr_tasks;
int t;
g->threads = zalloc_shared_data(size);
for (t = 0; t < g->p.nr_tasks; t++) {
struct thread_data *td = g->threads + t;
int cpu;
/* Allow all nodes by default: */
td->bind_node = NUMA_NO_NODE;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
/* Allow all CPUs by default: */
CPU_ZERO(&td->bind_cpumask);
for (cpu = 0; cpu < g->p.nr_cpus; cpu++)
CPU_SET(cpu, &td->bind_cpumask);
}
}
static void deinit_thread_data(void)
{
ssize_t size = sizeof(*g->threads)*g->p.nr_tasks;
free_data(g->threads, size);
}
static int init(void)
{
g = (void *)alloc_data(sizeof(*g), MAP_SHARED, 1, 0, 0 /* THP */, 0);
/* Copy over options: */
g->p = p0;
g->p.nr_cpus = numa_num_configured_cpus();
g->p.nr_nodes = numa_max_node() + 1;
/* char array in count_process_nodes(): */
BUG_ON(g->p.nr_nodes > MAX_NR_NODES || g->p.nr_nodes < 0);
if (g->p.show_quiet && !g->p.show_details)
g->p.show_details = -1;
/* Some memory should be specified: */
if (!g->p.mb_global_str && !g->p.mb_proc_str && !g->p.mb_thread_str)
return -1;
if (g->p.mb_global_str) {
g->p.mb_global = atof(g->p.mb_global_str);
BUG_ON(g->p.mb_global < 0);
}
if (g->p.mb_proc_str) {
g->p.mb_proc = atof(g->p.mb_proc_str);
BUG_ON(g->p.mb_proc < 0);
}
if (g->p.mb_proc_locked_str) {
g->p.mb_proc_locked = atof(g->p.mb_proc_locked_str);
BUG_ON(g->p.mb_proc_locked < 0);
BUG_ON(g->p.mb_proc_locked > g->p.mb_proc);
}
if (g->p.mb_thread_str) {
g->p.mb_thread = atof(g->p.mb_thread_str);
BUG_ON(g->p.mb_thread < 0);
}
BUG_ON(g->p.nr_threads <= 0);
BUG_ON(g->p.nr_proc <= 0);
g->p.nr_tasks = g->p.nr_proc*g->p.nr_threads;
g->p.bytes_global = g->p.mb_global *1024L*1024L;
g->p.bytes_process = g->p.mb_proc *1024L*1024L;
g->p.bytes_process_locked = g->p.mb_proc_locked *1024L*1024L;
g->p.bytes_thread = g->p.mb_thread *1024L*1024L;
g->data = setup_shared_data(g->p.bytes_global);
/* Startup serialization: */
init_global_mutex(&g->start_work_mutex);
init_global_mutex(&g->startup_mutex);
init_global_mutex(&g->startup_done_mutex);
init_global_mutex(&g->stop_work_mutex);
init_thread_data();
tprintf("#\n");
if (parse_setup_cpu_list() || parse_setup_node_list())
return -1;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
tprintf("#\n");
print_summary();
return 0;
}
static void deinit(void)
{
free_data(g->data, g->p.bytes_global);
g->data = NULL;
deinit_thread_data();
free_data(g, sizeof(*g));
g = NULL;
}
/*
* Print a short or long result, depending on the verbosity setting:
*/
static void print_res(const char *name, double val,
const char *txt_unit, const char *txt_short, const char *txt_long)
{
if (!name)
name = "main,";
if (!g->p.show_quiet)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
printf(" %-30s %15.3f, %-15s %s\n", name, val, txt_unit, txt_short);
else
printf(" %14.3f %s\n", val, txt_long);
}
static int __bench_numa(const char *name)
{
struct timeval start, stop, diff;
u64 runtime_ns_min, runtime_ns_sum;
pid_t *pids, pid, wpid;
double delta_runtime;
double runtime_avg;
double runtime_sec_max;
double runtime_sec_min;
int wait_stat;
double bytes;
int i, t, p;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
if (init())
return -1;
pids = zalloc(g->p.nr_proc * sizeof(*pids));
pid = -1;
/* All threads try to acquire it, this way we can wait for them to start up: */
pthread_mutex_lock(&g->start_work_mutex);
if (g->p.serialize_startup) {
tprintf(" #\n");
tprintf(" # Startup synchronization: ..."); fflush(stdout);
}
gettimeofday(&start, NULL);
for (i = 0; i < g->p.nr_proc; i++) {
pid = fork();
dprintf(" # process %2d: PID %d\n", i, pid);
BUG_ON(pid < 0);
if (!pid) {
/* Child process: */
worker_process(i);
exit(0);
}
pids[i] = pid;
}
/* Wait for all the threads to start up: */
while (g->nr_tasks_started != g->p.nr_tasks)
usleep(USEC_PER_MSEC);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
BUG_ON(g->nr_tasks_started != g->p.nr_tasks);
if (g->p.serialize_startup) {
double startup_sec;
pthread_mutex_lock(&g->startup_done_mutex);
/* This will start all threads: */
pthread_mutex_unlock(&g->start_work_mutex);
/* This mutex is locked - the last started thread will wake us: */
pthread_mutex_lock(&g->startup_done_mutex);
gettimeofday(&stop, NULL);
timersub(&stop, &start, &diff);
startup_sec = diff.tv_sec * NSEC_PER_SEC;
startup_sec += diff.tv_usec * NSEC_PER_USEC;
startup_sec /= NSEC_PER_SEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
tprintf(" threads initialized in %.6f seconds.\n", startup_sec);
tprintf(" #\n");
start = stop;
pthread_mutex_unlock(&g->startup_done_mutex);
} else {
gettimeofday(&start, NULL);
}
/* Parent process: */
for (i = 0; i < g->p.nr_proc; i++) {
wpid = waitpid(pids[i], &wait_stat, 0);
BUG_ON(wpid < 0);
BUG_ON(!WIFEXITED(wait_stat));
}
runtime_ns_sum = 0;
runtime_ns_min = -1LL;
for (t = 0; t < g->p.nr_tasks; t++) {
u64 thread_runtime_ns = g->threads[t].runtime_ns;
runtime_ns_sum += thread_runtime_ns;
runtime_ns_min = min(thread_runtime_ns, runtime_ns_min);
}
gettimeofday(&stop, NULL);
timersub(&stop, &start, &diff);
BUG_ON(bench_format != BENCH_FORMAT_DEFAULT);
tprintf("\n ###\n");
tprintf("\n");
runtime_sec_max = diff.tv_sec * NSEC_PER_SEC;
runtime_sec_max += diff.tv_usec * NSEC_PER_USEC;
runtime_sec_max /= NSEC_PER_SEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
runtime_sec_min = runtime_ns_min / NSEC_PER_SEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
bytes = g->bytes_done;
runtime_avg = (double)runtime_ns_sum / g->p.nr_tasks / NSEC_PER_SEC;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
if (g->p.measure_convergence) {
print_res(name, runtime_sec_max,
"secs,", "NUMA-convergence-latency", "secs latency to NUMA-converge");
}
print_res(name, runtime_sec_max,
"secs,", "runtime-max/thread", "secs slowest (max) thread-runtime");
print_res(name, runtime_sec_min,
"secs,", "runtime-min/thread", "secs fastest (min) thread-runtime");
print_res(name, runtime_avg,
"secs,", "runtime-avg/thread", "secs average thread-runtime");
delta_runtime = (runtime_sec_max - runtime_sec_min)/2.0;
print_res(name, delta_runtime / runtime_sec_max * 100.0,
"%,", "spread-runtime/thread", "% difference between max/avg runtime");
print_res(name, bytes / g->p.nr_tasks / 1e9,
"GB,", "data/thread", "GB data processed, per thread");
print_res(name, bytes / 1e9,
"GB,", "data-total", "GB data processed, total");
print_res(name, runtime_sec_max * NSEC_PER_SEC / (bytes / g->p.nr_tasks),
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
"nsecs,", "runtime/byte/thread","nsecs/byte/thread runtime");
print_res(name, bytes / g->p.nr_tasks / 1e9 / runtime_sec_max,
"GB/sec,", "thread-speed", "GB/sec/thread speed");
print_res(name, bytes / runtime_sec_max / 1e9,
"GB/sec,", "total-speed", "GB/sec total speed");
if (g->p.show_details >= 2) {
char tname[14 + 2 * 10 + 1];
struct thread_data *td;
for (p = 0; p < g->p.nr_proc; p++) {
for (t = 0; t < g->p.nr_threads; t++) {
memset(tname, 0, sizeof(tname));
td = g->threads + p*g->p.nr_threads + t;
snprintf(tname, sizeof(tname), "process%d:thread%d", p, t);
print_res(tname, td->speed_gbs,
"GB/sec", "thread-speed", "GB/sec/thread speed");
print_res(tname, td->system_time_ns / NSEC_PER_SEC,
"secs", "thread-system-time", "system CPU time/thread");
print_res(tname, td->user_time_ns / NSEC_PER_SEC,
"secs", "thread-user-time", "user CPU time/thread");
}
}
}
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
free(pids);
deinit();
return 0;
}
#define MAX_ARGS 50
static int command_size(const char **argv)
{
int size = 0;
while (*argv) {
size++;
argv++;
}
BUG_ON(size >= MAX_ARGS);
return size;
}
static void init_params(struct params *p, const char *name, int argc, const char **argv)
{
int i;
printf("\n # Running %s \"perf bench numa", name);
for (i = 0; i < argc; i++)
printf(" %s", argv[i]);
printf("\"\n");
memset(p, 0, sizeof(*p));
/* Initialize nonzero defaults: */
p->serialize_startup = 1;
p->data_reads = true;
p->data_writes = true;
p->data_backwards = true;
p->data_rand_walk = true;
p->nr_loops = -1;
p->init_random = true;
p->mb_global_str = "1";
p->nr_proc = 1;
p->nr_threads = 1;
p->nr_secs = 5;
p->run_all = argc == 1;
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
}
static int run_bench_numa(const char *name, const char **argv)
{
int argc = command_size(argv);
init_params(&p0, name, argc, argv);
argc = parse_options(argc, argv, options, bench_numa_usage, 0);
if (argc)
goto err;
if (__bench_numa(name))
goto err;
return 0;
err:
return -1;
}
#define OPT_BW_RAM "-s", "20", "-zZq", "--thp", " 1", "--no-data_rand_walk"
#define OPT_BW_RAM_NOTHP OPT_BW_RAM, "--thp", "-1"
#define OPT_CONV "-s", "100", "-zZ0qcm", "--thp", " 1"
#define OPT_CONV_NOTHP OPT_CONV, "--thp", "-1"
#define OPT_BW "-s", "20", "-zZ0q", "--thp", " 1"
#define OPT_BW_NOTHP OPT_BW, "--thp", "-1"
/*
* The built-in test-suite executed by "perf bench numa -a".
*
* (A minimum of 4 nodes and 16 GB of RAM is recommended.)
*/
static const char *tests[][MAX_ARGS] = {
/* Basic single-stream NUMA bandwidth measurements: */
{ "RAM-bw-local,", "mem", "-p", "1", "-t", "1", "-P", "1024",
"-C" , "0", "-M", "0", OPT_BW_RAM },
{ "RAM-bw-local-NOTHP,",
"mem", "-p", "1", "-t", "1", "-P", "1024",
"-C" , "0", "-M", "0", OPT_BW_RAM_NOTHP },
{ "RAM-bw-remote,", "mem", "-p", "1", "-t", "1", "-P", "1024",
"-C" , "0", "-M", "1", OPT_BW_RAM },
/* 2-stream NUMA bandwidth measurements: */
{ "RAM-bw-local-2x,", "mem", "-p", "2", "-t", "1", "-P", "1024",
"-C", "0,2", "-M", "0x2", OPT_BW_RAM },
{ "RAM-bw-remote-2x,", "mem", "-p", "2", "-t", "1", "-P", "1024",
"-C", "0,2", "-M", "1x2", OPT_BW_RAM },
/* Cross-stream NUMA bandwidth measurement: */
{ "RAM-bw-cross,", "mem", "-p", "2", "-t", "1", "-P", "1024",
"-C", "0,8", "-M", "1,0", OPT_BW_RAM },
/* Convergence latency measurements: */
{ " 1x3-convergence,", "mem", "-p", "1", "-t", "3", "-P", "512", OPT_CONV },
{ " 1x4-convergence,", "mem", "-p", "1", "-t", "4", "-P", "512", OPT_CONV },
{ " 1x6-convergence,", "mem", "-p", "1", "-t", "6", "-P", "1020", OPT_CONV },
{ " 2x3-convergence,", "mem", "-p", "3", "-t", "3", "-P", "1020", OPT_CONV },
{ " 3x3-convergence,", "mem", "-p", "3", "-t", "3", "-P", "1020", OPT_CONV },
{ " 4x4-convergence,", "mem", "-p", "4", "-t", "4", "-P", "512", OPT_CONV },
{ " 4x4-convergence-NOTHP,",
"mem", "-p", "4", "-t", "4", "-P", "512", OPT_CONV_NOTHP },
{ " 4x6-convergence,", "mem", "-p", "4", "-t", "6", "-P", "1020", OPT_CONV },
{ " 4x8-convergence,", "mem", "-p", "4", "-t", "8", "-P", "512", OPT_CONV },
{ " 8x4-convergence,", "mem", "-p", "8", "-t", "4", "-P", "512", OPT_CONV },
{ " 8x4-convergence-NOTHP,",
"mem", "-p", "8", "-t", "4", "-P", "512", OPT_CONV_NOTHP },
{ " 3x1-convergence,", "mem", "-p", "3", "-t", "1", "-P", "512", OPT_CONV },
{ " 4x1-convergence,", "mem", "-p", "4", "-t", "1", "-P", "512", OPT_CONV },
{ " 8x1-convergence,", "mem", "-p", "8", "-t", "1", "-P", "512", OPT_CONV },
{ "16x1-convergence,", "mem", "-p", "16", "-t", "1", "-P", "256", OPT_CONV },
{ "32x1-convergence,", "mem", "-p", "32", "-t", "1", "-P", "128", OPT_CONV },
/* Various NUMA process/thread layout bandwidth measurements: */
{ " 2x1-bw-process,", "mem", "-p", "2", "-t", "1", "-P", "1024", OPT_BW },
{ " 3x1-bw-process,", "mem", "-p", "3", "-t", "1", "-P", "1024", OPT_BW },
{ " 4x1-bw-process,", "mem", "-p", "4", "-t", "1", "-P", "1024", OPT_BW },
{ " 8x1-bw-process,", "mem", "-p", "8", "-t", "1", "-P", " 512", OPT_BW },
{ " 8x1-bw-process-NOTHP,",
"mem", "-p", "8", "-t", "1", "-P", " 512", OPT_BW_NOTHP },
{ "16x1-bw-process,", "mem", "-p", "16", "-t", "1", "-P", "256", OPT_BW },
{ " 4x1-bw-thread,", "mem", "-p", "1", "-t", "4", "-T", "256", OPT_BW },
{ " 8x1-bw-thread,", "mem", "-p", "1", "-t", "8", "-T", "256", OPT_BW },
{ "16x1-bw-thread,", "mem", "-p", "1", "-t", "16", "-T", "128", OPT_BW },
{ "32x1-bw-thread,", "mem", "-p", "1", "-t", "32", "-T", "64", OPT_BW },
{ " 2x3-bw-thread,", "mem", "-p", "2", "-t", "3", "-P", "512", OPT_BW },
{ " 4x4-bw-thread,", "mem", "-p", "4", "-t", "4", "-P", "512", OPT_BW },
{ " 4x6-bw-thread,", "mem", "-p", "4", "-t", "6", "-P", "512", OPT_BW },
{ " 4x8-bw-thread,", "mem", "-p", "4", "-t", "8", "-P", "512", OPT_BW },
{ " 4x8-bw-thread-NOTHP,",
"mem", "-p", "4", "-t", "8", "-P", "512", OPT_BW_NOTHP },
{ " 3x3-bw-thread,", "mem", "-p", "3", "-t", "3", "-P", "512", OPT_BW },
{ " 5x5-bw-thread,", "mem", "-p", "5", "-t", "5", "-P", "512", OPT_BW },
{ "2x16-bw-thread,", "mem", "-p", "2", "-t", "16", "-P", "512", OPT_BW },
{ "1x32-bw-thread,", "mem", "-p", "1", "-t", "32", "-P", "2048", OPT_BW },
{ "numa02-bw,", "mem", "-p", "1", "-t", "32", "-T", "32", OPT_BW },
{ "numa02-bw-NOTHP,", "mem", "-p", "1", "-t", "32", "-T", "32", OPT_BW_NOTHP },
{ "numa01-bw-thread,", "mem", "-p", "2", "-t", "16", "-T", "192", OPT_BW },
{ "numa01-bw-thread-NOTHP,",
"mem", "-p", "2", "-t", "16", "-T", "192", OPT_BW_NOTHP },
};
static int bench_all(void)
{
int nr = ARRAY_SIZE(tests);
int ret;
int i;
ret = system("echo ' #'; echo ' # Running test on: '$(uname -a); echo ' #'");
BUG_ON(ret < 0);
for (i = 0; i < nr; i++) {
run_bench_numa(tests[i][0], tests[i] + 1);
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
}
printf("\n");
return 0;
}
int bench_numa(int argc, const char **argv)
perf: Add 'perf bench numa mem' NUMA performance measurement suite Add a suite of NUMA performance benchmarks. The goal was simulate the behavior and access patterns of real NUMA workloads, via a wide range of parameters, so this tool goes well beyond simple bzero() measurements that most NUMA micro-benchmarks use: - It processes the data and creates a chain of data dependencies, like a real workload would. Neither the compiler, nor the kernel (via KSM and other optimizations) nor the CPU can eliminate parts of the workload. - It randomizes the initial state and also randomizes the target addresses of the processing - it's not a simple forward scan of addresses. - It provides flexible options to set process, thread and memory relationship information: -G sets "global" memory shared between all test processes, -P sets "process" memory shared by all threads of a process and -T sets "thread" private memory. - There's a NUMA convergence monitoring and convergence latency measurement option via -c and -m. - Micro-sleeps and synchronization can be injected to provoke lock contention and scheduling, via the -u and -S options. This simulates IO and contention. - The -x option instructs the workload to 'perturb' itself artificially every N seconds, by moving to the first and last CPU of the system periodically. This way the stability of convergence equilibrium and the number of steps taken for the scheduler to reach equilibrium again can be measured. - The amount of work can be specified via the -l loop count, and/or via a -s seconds-timeout value. - CPU and node memory binding options, to test hard binding scenarios. THP can be turned on and off via madvise() calls. - Live reporting of convergence progress in an 'at glance' output format. Printing of convergence and deconvergence events. The 'perf bench numa mem -a' option will start an array of about 30 individual tests that will each output such measurements: # Running 5x5-bw-thread, "perf bench numa mem -p 5 -t 5 -P 512 -s 20 -zZ0q --thp 1" 5x5-bw-thread, 20.276, secs, runtime-max/thread 5x5-bw-thread, 20.004, secs, runtime-min/thread 5x5-bw-thread, 20.155, secs, runtime-avg/thread 5x5-bw-thread, 0.671, %, spread-runtime/thread 5x5-bw-thread, 21.153, GB, data/thread 5x5-bw-thread, 528.818, GB, data-total 5x5-bw-thread, 0.959, nsecs, runtime/byte/thread 5x5-bw-thread, 1.043, GB/sec, thread-speed 5x5-bw-thread, 26.081, GB/sec, total-speed See the help text and the code for more details. Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Arnaldo Carvalho de Melo <acme@redhat.com> Cc: Frederic Weisbecker <fweisbec@gmail.com> Cc: Mike Galbraith <efault@gmx.de> Cc: Steven Rostedt <rostedt@goodmis.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Andrea Arcangeli <aarcange@redhat.com> Cc: Rik van Riel <riel@redhat.com> Cc: Mel Gorman <mgorman@suse.de> Cc: Hugh Dickins <hughd@google.com> Signed-off-by: Ingo Molnar <mingo@kernel.org>
2012-12-06 19:51:59 +07:00
{
init_params(&p0, "main,", argc, argv);
argc = parse_options(argc, argv, options, bench_numa_usage, 0);
if (argc)
goto err;
if (p0.run_all)
return bench_all();
if (__bench_numa(NULL))
goto err;
return 0;
err:
usage_with_options(numa_usage, options);
return -1;
}