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run.py
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run.py
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#!/usr/bin/env python3
import random
import itertools
import click
from backends import (
__backends__ as setup_functions,
check_backend_conflicts,
convert_to_numpy,
BackendNotSupported,
BackendConflict,
)
from utilities import (
Timer,
estimate_repetitions,
format_output,
compute_statistics,
get_benchmark_module,
check_consistency,
)
DEFAULT_SIZE = tuple(2 ** i for i in range(12, 23, 2))
@click.command("run")
@click.argument(
"BENCHMARK",
required=True,
type=click.Path(exists=True, file_okay=False, readable=True),
)
@click.option(
"-s",
"--size",
required=False,
multiple=True,
default=DEFAULT_SIZE,
show_default=True,
type=click.INT,
help="Run benchmark for this array size (repeatable)",
)
@click.option(
"-b",
"--backend",
required=False,
multiple=True,
default=None,
type=click.Choice(setup_functions.keys()),
help="Run benchmark with this backend (repeatable) [default: run all backends]",
)
@click.option(
"-r",
"--repetitions",
required=False,
default=None,
type=click.INT,
help="Fixed number of iterations to run for each size and backend [default: auto-detect]",
)
@click.option(
"--burnin",
required=False,
default=1,
type=click.INT,
show_default=True,
help="Number of initial iterations that are disregarded for final statistics",
)
@click.option(
"--device",
required=False,
default="cpu",
type=click.Choice(["cpu", "gpu", "tpu"]),
show_default=True,
help="Run benchmarks on given device where supported by the backend",
)
def main(benchmark, size=None, backend=None, repetitions=None, burnin=1, device="cpu"):
"""HPC benchmarks for Python
Usage:
$ python run.py benchmarks/<BENCHMARK_FOLDER>
Examples:
$ taskset -c 0 python run.py benchmarks/equation_of_state
$ python run.py benchmarks/equation_of_state -b numpy -b jax --device gpu
More information:
https://github.com/dionhaefner/pyhpc-benchmarks
"""
try:
bm_module, bm_identifier = get_benchmark_module(benchmark)
except ImportError as e:
click.echo(f"Error while loading benchmark {benchmark}: {e!s}", err=True)
raise click.Abort()
available_backends = set(bm_module.__implementations__)
if len(backend) == 0:
backend = available_backends.copy()
else:
backend = set(backend)
unsupported_backends = [b for b in backend if b not in available_backends]
for b in unsupported_backends:
click.echo(
f'Backend "{b}" is not supported by chosen benchmark (skipping)', err=True
)
backend.remove(b)
for b in backend.copy():
try:
with setup_functions[b](device=device) as bmod:
click.echo(f"Using {b} version {bmod.__version__}")
except BackendNotSupported as e:
click.echo(
f'Setup for backend "{b}" failed (skipping), reason: {e!s}', err=True
)
backend.remove(b)
try:
check_backend_conflicts(backend, device)
except BackendConflict as exc:
click.echo(f"Backend conflict: {exc!s}", err=True)
raise click.Abort()
runs = sorted(itertools.product(backend, size))
if len(runs) == 0:
click.echo("Nothing to do")
return
timings = {run: [] for run in runs}
if repetitions is None:
click.echo("Estimating repetitions...")
repetitions = {}
for b, s in runs:
# use end-to-end runtime for repetition estimation
def run_func():
run = bm_module.get_callable(b, s, device=device)
with setup_functions[b](device=device):
run()
repetitions[(b, s)] = estimate_repetitions(run_func)
else:
repetitions = {(b, s): repetitions for b, s in runs}
all_runs = list(
itertools.chain.from_iterable(
[run] * (repetitions[run] + burnin) for run in runs
)
)
random.shuffle(all_runs)
results = {}
checked = {r: False for r in runs}
pbar = click.progressbar(
label=f"Running {len(all_runs)} benchmarks...", length=len(runs)
)
try:
with pbar:
for (b, size) in all_runs:
with setup_functions[b](device=device):
run = bm_module.get_callable(b, size, device=device)
with Timer() as t:
res = run()
# YOWO (you only warn once)
if not checked[(b, size)]:
if size in results:
is_consistent = check_consistency(
results[size], convert_to_numpy(res, b, device)
)
if not is_consistent:
click.echo(
f"\nWarning: inconsistent results for size {size}",
err=True,
)
else:
results[size] = convert_to_numpy(res, b, device)
checked[(b, size)] = True
timings[(b, size)].append(t.elapsed)
pbar.update(1.0 / (repetitions[(b, size)] + burnin))
# push pbar to 100%
pbar.update(1.0)
for run in runs:
assert len(timings[run]) == repetitions[run] + burnin
finally:
stats = compute_statistics(timings)
click.echo(format_output(stats, bm_identifier, device=device))
if __name__ == "__main__":
main()