Re: [RFC][PATCH 00/11] perf pmu interface -v2

[Peter Zijlstra <peterz@infradead.org>]

On Thu, 2010-07-01 at 17:39 +0200, Peter Zijlstra wrote:
> 
> Ah, for sampling for sure, simply group a software perf event and a
> hardware perf event together and use PERF_SAMPLE_READ. 

So the idea is to sample using a software event (periodic timer of
sorts, maybe randomize it) and weight its samples by the hardware event
deltas.

Suppose you have a workload consisting of two main parts:

  my_important_work()
  {
     load_my_data();
     compute_me_silly();
  }

Now, lets assume that both these functions take the same time to
complete for each part of work. In that case a periodic timer generate
samples that are about 50/50 distributed between these two functions.

Now, let us further assume that load_my_data() is so slow because its
missing all the caches and compute_me_silly() is slow because its
defeating the branch predictor.

So what we want to end up with, is that when we sample for cache-misses
we get load_my_data() as the predominant function, not a nice 50/50
relation. Idem for branch misses and compute_me_silly().

By weighting the samples by the hw counter delta we get this, if we
assume that the sampling frequency is not a harmonic of the runtime of
these functions, then statistics will dtrt.

It basically generates a massive skid on the sample, but as long as most
of the samples end up hitting the right function we're good. For a
periodic workload like: 
  while (lots) { my_important_work() }
that is even true for period > function_runtime with the exception of
that harmonic thing. For less neat workloads like:
  while (lots) { my_important_work(); other_random_things(); }
This doesn't need to work unless period < function_runtime.

Clearly we cannot attribute anything to the actual instruction hit due
to the massive skid, but we can (possibly) say something about the
function based on these statistical rules.