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Subject[generalized cache events] Re: [PATCH 1/1] perf tools: Add missing user space support for config1/config2

* Stephane Eranian <eranian@google.com> wrote:

> >> Generic cache events are a myth. They are not usable. [...]
> >
> > Well:
> >
> >  aldebaran:~> perf stat --repeat 10 -e instructions -e L1-dcache-loads -e L1-dcache-load-misses -e LLC-misses ./hackbench 10
> >  Time: 0.125
> >  Time: 0.136
> >  Time: 0.180
> >  Time: 0.103
> >  Time: 0.097
> >  Time: 0.125
> >  Time: 0.104
> >  Time: 0.125
> >  Time: 0.114
> >  Time: 0.158
> >
> >  Performance counter stats for './hackbench 10' (10 runs):
> >
> >     2,102,556,398 instructions             #      0.000 IPC     ( +-   1.179% )
> >       843,957,634 L1-dcache-loads            ( +-   1.295% )
> >       130,007,361 L1-dcache-load-misses      ( +-   3.281% )
> >         6,328,938 LLC-misses                 ( +-   3.969% )
> >
> >        0.146160287  seconds time elapsed   ( +-   5.851% )
> >
> > It's certainly useful if you want to get ballpark figures about cache behavior
> > of an app and want to do comparisons.
> >
> What can you conclude from the above counts?
> Are they good or bad? If they are bad, how do you go about fixing the app?

So let me give you a simplified example.

Say i'm a developer and i have an app with such code:

#define THOUSAND 1000

static char array[THOUSAND][THOUSAND];

int init_array(void)
{
int i, j;

for (i = 0; i < THOUSAND; i++) {
for (j = 0; j < THOUSAND; j++) {
array[j][i]++;
}
}

return 0;
}

Pretty common stuff, right?

Using the generalized cache events i can run:

$ perf stat --repeat 10 -e cycles:u -e instructions:u -e l1-dcache-loads:u -e l1-dcache-load-misses:u ./array

Performance counter stats for './array' (10 runs):

6,719,130 cycles:u ( +- 0.662% )
5,084,792 instructions:u # 0.757 IPC ( +- 0.000% )
1,037,032 l1-dcache-loads:u ( +- 0.009% )
1,003,604 l1-dcache-load-misses:u ( +- 0.003% )

0.003802098 seconds time elapsed ( +- 13.395% )

I consider that this is 'bad', because for almost every dcache-load there's a
dcache-miss - a 99% L1 cache miss rate!

Then i think a bit, notice something, apply this performance optimization:

diff --git a/array.c b/array.c
index 4758d9a..d3f7037 100644
--- a/array.c
+++ b/array.c
@@ -9,7 +9,7 @@ int init_array(void)

for (i = 0; i < THOUSAND; i++) {
for (j = 0; j < THOUSAND; j++) {
- array[j][i]++;
+ array[i][j]++;
}
}

I re-run perf-stat:
$ perf stat --repeat 10 -e cycles:u -e instructions:u -e l1-dcache-loads:u -e l1-dcache-load-misses:u ./array

Performance counter stats for './array' (10 runs):

2,395,407 cycles:u ( +- 0.365% )
5,084,788 instructions:u # 2.123 IPC ( +- 0.000% )
1,035,731 l1-dcache-loads:u ( +- 0.006% )
3,955 l1-dcache-load-misses:u ( +- 4.872% )

0.001806438 seconds time elapsed ( +- 3.831% )

And i'm happy that indeed the l1-dcache misses are now super-low and that the
app got much faster as well - the cycle count is a third of what it was before
the optimization!

Note that:

- I got absolute numbers in the right ballpark figure: i got a million loads as
expected (the array has 1 million elements), and 1 million cache-misses in
the 'bad' case.

- I did not care which specific Intel CPU model this was running on

- I did not care about *any* microarchitectural details - i only knew it's a
reasonably modern CPU with caching

- I did not care how i could get access to L1 load and miss events. The events
were named obviously and it just worked.

So no, kernel driven generalization and sane tooling is not at all a 'myth'
today, really.

So this is the general direction in which we want to move on. If you know about
problems with existing generalization definitions then lets *fix* them, not
pretend that generalizations and sane workflows are impossible ...

Thanks,

Ingo
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