Expensive setup code repeated too often

[Dennis Sweeney]

When I run the benchmark below, I notice that most of the time is spent in the zipf_string() function, I think re-creating the relevant strings in each and every spawned process. Putting a print() inside zipf_string() prints continuously. This is significant, especially when running 20*16*5==1600 benchmarks. Is there a recommended way to cache expensively-generated parameters so that each process does not have to create them from scratch?

I am also generally confused about the multiprocessing model of pyperf: I would expect zipf_string to be called exactly twice (not hundreds of times) per benchmark. I couldn't find anything in the documentation about this. Am I missing something? I am running Windows 10.

from random import Random
import pyperf

# shuffled alphabet
alphabet = 'DHUXYEZQCLFKISBVRGNAMWPTOJ'
zipf = [1/x for x in range(1, 1+len(alphabet))]

def zipf_string(length, seed):
    letters = Random(seed).choices(alphabet, weights=zipf, k=length)
    return ''.join(letters)

needle_lengths = [
    2, 3, 4, 6,
    8, 12, 16, 24,
    32, 48, 64, 96,
    128, 192, 256, 384,
    512, 768, 1024, 1536,
]

haystack_lengths = [
    500, 750, 1000, 1500,
    2000, 3000, 4000, 6000,
    8000, 12000, 16000, 24000,
    32000, 48000, 64000, 96000,
]

def bench(loops, needle, haystack):
    range_it = range(loops)
    t0 = pyperf.perf_counter()

    for _ in range_it:
        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)

        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)
        haystack.count(needle)

    return pyperf.perf_counter() - t0

def do_timings():
    import pyperf
    runner = pyperf.Runner()

    for m in needle_lengths:
        for n in haystack_lengths:
            if n < m:
                continue
            for s in (1, 2, 3, 4, 5):
                seed = (s*n + m) % 1_000_003
                needle = zipf_string(m, seed)
                haystack = zipf_string(n, seed ** 2)
                runner.bench_time_func(
                    f"needle={m}, haystack={n}, seed={s}",
                    bench, needle, haystack,
                    inner_loops=10,
                )

if __name__ == "__main__":
    do_timings()

[Dennis Sweeney]

For what it's worth, I wound up using two different programs, one to generate the benchmarks, and one to run them:

...

def generate_benchmarks():
    output = []
    for m in needle_lengths:
        for n in haystack_lengths:
            if n < m:
                continue
            for s in (1, 2, 3):
                seed = (s*n + m) % 1_000_003
                needle = zipf_string(m, seed)
                haystack = zipf_string(n, seed ** 2)
                name = f"needle={m}, haystack={n}, seed={s}"
                output.append((name, needle, haystack))
    with open("_generated.py", 'w') as f:
        print("benches = [", file=f)
        for name, needle, haystack in output:
            print(f"    {(name, needle, haystack)!r},", file=f)
        print("]", file=f)

...

def do_timings():
    import pyperf
    runner = pyperf.Runner()

    from _generated import benches

    for name, needle, haystack in benches:
        runner.bench_time_func(
            name,
            bench, needle, haystack,
            inner_loops=10,
        )

if __name__ == "__main__":
    # generate_benchmarks()
    do_timings()

[Dennis Sweeney]

Closing as a duplicate of #38