Perf examples
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− | First, discovery/enumeration of available counters can be done via | + | First, discovery/enumeration of available counters can be done via 'perf |
− | 'perf list': | + | list'. (For the tracepoint events you will need to have debugfs mounted |
+ | first, e.g. <tt>mount -t debugfs none /dbg</tt>): | ||
− | titan:~> perf list | + | titan:~> perf list |
[...] | [...] | ||
kmem:kmalloc [Tracepoint event] | kmem:kmalloc [Tracepoint event] |
Latest revision as of 16:59, 8 November 2009
First, discovery/enumeration of available counters can be done via 'perf list'. (For the tracepoint events you will need to have debugfs mounted first, e.g. mount -t debugfs none /dbg):
titan:~> perf list [...] kmem:kmalloc [Tracepoint event] kmem:kmem_cache_alloc [Tracepoint event] kmem:kmalloc_node [Tracepoint event] kmem:kmem_cache_alloc_node [Tracepoint event] kmem:kfree [Tracepoint event] kmem:kmem_cache_free [Tracepoint event] kmem:mm_page_free_direct [Tracepoint event] kmem:mm_pagevec_free [Tracepoint event] kmem:mm_page_alloc [Tracepoint event] kmem:mm_page_alloc_zone_locked [Tracepoint event] kmem:mm_page_pcpu_drain [Tracepoint event] kmem:mm_page_alloc_extfrag [Tracepoint event]
Then any (or all) of the above event sources can be activated and measured. For example the page alloc/free properties of a 'hackbench run' are:
titan:~> perf stat -e kmem:mm_page_pcpu_drain -e kmem:mm_page_alloc -e kmem:mm_pagevec_free -e kmem:mm_page_free_direct ./hackbench 10 Time: 0.575 Performance counter stats for './hackbench 10': 13857 kmem:mm_page_pcpu_drain 27576 kmem:mm_page_alloc 6025 kmem:mm_pagevec_free 20934 kmem:mm_page_free_direct 0.613972165 seconds time elapsed
You can observe the statistical properties as well, by using the 'repeat the workload N times' feature of perf stat:
titan:~> perf stat --repeat 5 -e kmem:mm_page_pcpu_drain -e kmem:mm_page_alloc -e kmem:mm_pagevec_free -e kmem:mm_page_free_direct ./hackbench 10 Time: 0.627 Time: 0.644 Time: 0.564 Time: 0.559 Time: 0.626
Performance counter stats for './hackbench 10' (5 runs): 12920 kmem:mm_page_pcpu_drain ( +- 3.359% ) 25035 kmem:mm_page_alloc ( +- 3.783% ) 6104 kmem:mm_pagevec_free ( +- 0.934% ) 18376 kmem:mm_page_free_direct ( +- 4.941% ) 0.643954516 seconds time elapsed ( +- 2.363% )
Furthermore, these tracepoints can be used to sample the workload as well. For example the page allocations done by a 'git gc' can be captured the following way:
titan:~/git> perf record -f -e kmem:mm_page_alloc -c 1 ./git gc Counting objects: 1148, done. Delta compression using up to 2 threads. Compressing objects: 100% (450/450), done. Writing objects: 100% (1148/1148), done. Total 1148 (delta 690), reused 1148 (delta 690) [ perf record: Captured and wrote 0.267 MB perf.data (~11679 samples) ]
To check which functions generated page allocations:
titan:~/git> perf report # Samples: 10646 # # Overhead Command Shared Object # ........ ............... .......................... # 23.57% git-repack /lib64/libc-2.5.so 21.81% git /lib64/libc-2.5.so 14.59% git ./git 11.79% git-repack ./git 7.12% git /lib64/ld-2.5.so 3.16% git-repack /lib64/libpthread-2.5.so 2.09% git-repack /bin/bash 1.97% rm /lib64/libc-2.5.so 1.39% mv /lib64/ld-2.5.so 1.37% mv /lib64/libc-2.5.so 1.12% git-repack /lib64/ld-2.5.so 0.95% rm /lib64/ld-2.5.so 0.90% git-update-serv /lib64/libc-2.5.so 0.73% git-update-serv /lib64/ld-2.5.so 0.68% perf /lib64/libpthread-2.5.so 0.64% git-repack /usr/lib64/libz.so.1.2.3
Or to see it on a more finegrained level:
titan:~/git> perf report --sort comm,dso,symbol
# Samples: 10646 # # Overhead Command Shared Object Symbol # ........ ............... .......................... ...... # 9.35% git-repack ./git [.] insert_obj_hash 9.12% git ./git [.] insert_obj_hash 7.31% git /lib64/libc-2.5.so [.] memcpy 6.34% git-repack /lib64/libc-2.5.so [.] _int_malloc 6.24% git-repack /lib64/libc-2.5.so [.] memcpy 5.82% git-repack /lib64/libc-2.5.so [.] __GI___fork 5.47% git /lib64/libc-2.5.so [.] _int_malloc 2.99% git /lib64/libc-2.5.so [.] memset
Furthermore, call-graph sampling can be done too, of page allocations - to see precisely what kind of page allocations there are:
titan:~/git> perf record -f -g -e kmem:mm_page_alloc -c 1 ./git gc Counting objects: 1148, done. Delta compression using up to 2 threads. Compressing objects: 100% (450/450), done. Writing objects: 100% (1148/1148), done. Total 1148 (delta 690), reused 1148 (delta 690) [ perf record: Captured and wrote 0.963 MB perf.data (~42069 samples) ]
titan:~/git> perf report -g # Samples: 10686 # # Overhead Command Shared Object # ........ ............... .......................... # 23.25% git-repack /lib64/libc-2.5.so | |--50.00%-- _int_free | |--37.50%-- __GI___fork | make_child | |--12.50%-- ptmalloc_unlock_all2 | make_child | --6.25%-- __GI_strcpy 21.61% git /lib64/libc-2.5.so | |--30.00%-- __GI_read | | | --83.33%-- git_config_from_file | git_config | | [...]
Or you can observe the whole system's page allocations for 10 seconds:
titan:~/git> perf stat -a -e kmem:mm_page_pcpu_drain -e kmem:mm_page_alloc -e kmem:mm_pagevec_free -e kmem:mm_page_free_direct sleep 10
Performance counter stats for 'sleep 10':
171585 kmem:mm_page_pcpu_drain 322114 kmem:mm_page_alloc 73623 kmem:mm_pagevec_free 254115 kmem:mm_page_free_direct 10.000591410 seconds time elapsed
Or observe how fluctuating the page allocations are, via statistical analysis done over ten 1-second intervals:
titan:~/git> perf stat --repeat 10 -a -e kmem:mm_page_pcpu_drain -e kmem:mm_page_alloc -e kmem:mm_pagevec_free -e kmem:mm_page_free_direct sleep 1
Performance counter stats for 'sleep 1' (10 runs): 17254 kmem:mm_page_pcpu_drain ( +- 3.709% ) 34394 kmem:mm_page_alloc ( +- 4.617% ) 7509 kmem:mm_pagevec_free ( +- 4.820% ) 25653 kmem:mm_page_free_direct ( +- 3.672% ) 1.058135029 seconds time elapsed ( +- 3.089% )
Or you can annotate the recorded 'git gc' run on a per symbol basis and check which instructions/source-code generated page allocations:
titan:~/git> perf annotate __GI___fork ------------------------------------------------ Percent | Source code & Disassembly of libc-2.5.so ------------------------------------------------ : : : Disassembly of section .plt: : Disassembly of section .text: : : 00000031a2e95560 <__fork>: [...] 0.00 : 31a2e95602: b8 38 00 00 00 mov $0x38,%eax 0.00 : 31a2e95607: 0f 05 syscall 83.42 : 31a2e95609: 48 3d 00 f0 ff ff cmp $0xfffffffffffff000,%rax 0.00 : 31a2e9560f: 0f 87 4d 01 00 00 ja 31a2e95762 <__fork+0x202> 0.00 : 31a2e95615: 85 c0 test %eax,%eax
( this shows that 83.42% of __GI___fork's page allocations come from the 0x38 system call it performs. )
[edit] Is it worth optimizing some particular function?
Suppose you want to know whether optimizing some particular function in your program is worth the effort. For example, in the git mailing list the idea of optimizing the SHA1 encryption routine came up, and one can use 'perf' to decide about it. See Linus' reply [1]:
"perf report --sort comm,dso,symbol" profiling shows the following for 'git fsck --full' on the kernel repo, using the Mozilla SHA1: 47.69% git /home/torvalds/git/git [.] moz_SHA1_Update 22.98% git /lib64/libz.so.1.2.3 [.] inflate_fast 7.32% git /lib64/libc-2.10.1.so [.] __GI_memcpy 4.66% git /lib64/libz.so.1.2.3 [.] inflate 3.76% git /lib64/libz.so.1.2.3 [.] adler32 2.86% git /lib64/libz.so.1.2.3 [.] inflate_table 2.41% git /home/torvalds/git/git [.] lookup_object 1.31% git /lib64/libc-2.10.1.so [.] _int_malloc 0.84% git /home/torvalds/git/git [.] patch_delta 0.78% git [kernel] [k] hpet_next_event so yeah, SHA1 performance matters.
[edit] Measuring latency
(from http://marc.info/?l=linux-kernel&m=125236192700449&w=2)
btw., if you run -tip and have these enabled:
CONFIG_PERF_COUNTER=y CONFIG_EVENT_TRACING=y
cd tools/perf/ make -j install
... then you can use a couple of new perfcounters features to measure scheduler latencies. For example:
perf stat -e sched:sched_stat_wait -e task-clock ./hackbench 20
Will tell you how many times this workload got delayed by waiting for CPU time.
You can repeat the workload as well and see the statistical properties of those metrics:
aldebaran:/home/mingo> perf stat --repeat 10 -e \ sched:sched_stat_wait:r -e task-clock ./hackbench 20 Time: 0.251 Time: 0.214 Time: 0.254 Time: 0.278 Time: 0.245 Time: 0.308 Time: 0.242 Time: 0.222 Time: 0.268 Time: 0.244
Performance counter stats for './hackbench 20' (10 runs):
59826 sched:sched_stat_wait # 0.026 M/sec ( +- 5.540% ) 2280.099643 task-clock-msecs # 7.525 CPUs ( +- 1.620% )
0.303013390 seconds time elapsed ( +- 3.189% )
To get scheduling events, do:
# perf list 2>&1 | grep sched: sched:sched_kthread_stop [Tracepoint event] sched:sched_kthread_stop_ret [Tracepoint event] sched:sched_wait_task [Tracepoint event] sched:sched_wakeup [Tracepoint event] sched:sched_wakeup_new [Tracepoint event] sched:sched_switch [Tracepoint event] sched:sched_migrate_task [Tracepoint event] sched:sched_process_free [Tracepoint event] sched:sched_process_exit [Tracepoint event] sched:sched_process_wait [Tracepoint event] sched:sched_process_fork [Tracepoint event] sched:sched_signal_send [Tracepoint event] sched:sched_stat_wait [Tracepoint event] sched:sched_stat_sleep [Tracepoint event] sched:sched_stat_iowait [Tracepoint event]
stat_wait/sleep/iowait would be the interesting ones, for latency analysis.
Or, if you want to see all the specific delays and want to see min/max/avg, you can do:
perf record -e sched:sched_stat_wait:r -f -R -c 1 ./hackbench 20 perf trace