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author | Ingo Molnar <mingo@elte.hu> | 2009-06-15 11:24:38 +0200 |
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committer | Ingo Molnar <mingo@elte.hu> | 2009-06-15 15:58:03 +0200 |
commit | 3dfabc74c65904c9e6cf952391312d16ea772ef5 (patch) | |
tree | e9b42a66aa6913cd811c0157aee521fc84b055ec /sound | |
parent | 74193ef0ecab92535c8517f082f1f50504526c9b (diff) |
perf report: Add per system call overhead histogram
Take advantage of call-graph percounter sampling/recording to
display a non-trivial histogram: the true, collapsed/summarized
cost measurement, on a per system call total overhead basis:
aldebaran:~/linux/linux/tools/perf> ./perf record -g -a -f ~/hackbench 10
aldebaran:~/linux/linux/tools/perf> ./perf report -s symbol --syscalls | head -10
#
# (3536 samples)
#
# Overhead Symbol
# ........ ......
#
40.75% [k] sys_write
40.21% [k] sys_read
4.44% [k] do_nmi
...
This is done by accounting each (reliable) call-chain that chains back
to a given system call to that system call function.
[ So in the above example we can see that hackbench spends about 40% of
its total time somewhere in sys_write() and 40% somewhere in
sys_read(), the rest of the time is spent in user-space. The time
is not spent in sys_write() _itself_ but in one of its many child
functions. ]
Or, a recording of a (source files are already in the page-cache) kernel build:
$ perf record -g -m 512 -f -- make -j32 kernel
$ perf report -s s --syscalls | grep '\[k\]' | grep -v nmi
4.14% [k] do_page_fault
1.20% [k] sys_write
1.10% [k] sys_open
0.63% [k] sys_exit_group
0.48% [k] smp_apic_timer_interrupt
0.37% [k] sys_read
0.37% [k] sys_execve
0.20% [k] sys_mmap
0.18% [k] sys_close
0.14% [k] sys_munmap
0.13% [k] sys_poll
0.09% [k] sys_newstat
0.07% [k] sys_clone
0.06% [k] sys_newfstat
0.05% [k] sys_access
0.05% [k] schedule
Shows the true total cost of each syscall variant that gets used
during a kernel build. This profile reveals it that pagefaults are
the costliest, followed by read()/write().
An interesting detail: timer interrupts cost 0.5% - or 0.5 seconds
per 100 seconds of kernel build-time. (this was done with HZ=1000)
The summary is done in 'perf report', i.e. in the post-processing
stage - so once we have a good call-graph recording, this type of
non-trivial high-level analysis becomes possible.
Cc: Peter Zijlstra <a.p.zijlstra@chello.nl>
Cc: Mike Galbraith <efault@gmx.de>
Cc: Paul Mackerras <paulus@samba.org>
Cc: Arnaldo Carvalho de Melo <acme@redhat.com>
Cc: Linus Torvalds <torvalds@linux-foundation.org>
Cc: Frederic Weisbecker <fweisbec@gmail.com>
Cc: Pekka Enberg <penberg@cs.helsinki.fi>
LKML-Reference: <new-submission>
Signed-off-by: Ingo Molnar <mingo@elte.hu>
Diffstat (limited to 'sound')
0 files changed, 0 insertions, 0 deletions