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




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