grpc/tools/profiling/microbenchmarks/bm_diff/bm_run.py

#!/usr/bin/env python3
#
# Copyright 2017 gRPC authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" Python utility to run opt and counters benchmarks and save json output """

import argparse
import itertools
import multiprocessing
import os
import random
import subprocess
import sys

import bm_constants
import jobset

sys.path.append(
    os.path.join(
        os.path.dirname(sys.argv[0]),
        "..",
        "..",
        "..",
        "run_tests",
        "python_utils",
    )
)


def _args():
    argp = argparse.ArgumentParser(description="Runs microbenchmarks")
    argp.add_argument(
        "-b",
        "--benchmarks",
        nargs="+",
        choices=bm_constants._AVAILABLE_BENCHMARK_TESTS,
        default=bm_constants._AVAILABLE_BENCHMARK_TESTS,
        help="Benchmarks to run",
    )
    argp.add_argument(
        "-j",
        "--jobs",
        type=int,
        default=multiprocessing.cpu_count(),
        help="Number of CPUs to use",
    )
    argp.add_argument(
        "-n",
        "--name",
        type=str,
        help=(
            "Unique name of the build to run. Needs to match the handle passed"
            " to bm_build.py"
        ),
    )
    argp.add_argument(
        "-r",
        "--regex",
        type=str,
        default="",
        help="Regex to filter benchmarks run",
    )
    argp.add_argument(
        "-l",
        "--loops",
        type=int,
        default=20,
        help=(
            "Number of times to loops the benchmarks. More loops cuts down on"
            " noise"
        ),
    )
    argp.add_argument("--counters", dest="counters", action="store_true")
    argp.add_argument("--no-counters", dest="counters", action="store_false")
    argp.set_defaults(counters=True)
    args = argp.parse_args()
    assert args.name
    if args.loops < 3:
        print(
            "WARNING: This run will likely be noisy. Increase loops to at "
            "least 3."
        )
    return args


def _collect_bm_data(bm, cfg, name, regex, idx, loops):
    jobs_list = []
    for line in subprocess.check_output(
        [
            "bm_diff_%s/%s/%s" % (name, cfg, bm),
            "--benchmark_list_tests",
            "--benchmark_filter=%s" % regex,
        ]
    ).splitlines():
        line = line.decode("UTF-8")
        stripped_line = (
            line.strip()
            .replace("/", "_")
            .replace("<", "_")
            .replace(">", "_")
            .replace(", ", "_")
        )
        cmd = [
            "bm_diff_%s/%s/%s" % (name, cfg, bm),
            "--benchmark_filter=^%s$" % line,
            "--benchmark_out=%s.%s.%s.%s.%d.json"
            % (bm, stripped_line, cfg, name, idx),
            "--benchmark_out_format=json",
        ]
        jobs_list.append(
            jobset.JobSpec(
                cmd,
                shortname="%s %s %s %s %d/%d"
                % (bm, line, cfg, name, idx + 1, loops),
                verbose_success=True,
                cpu_cost=2,
                timeout_seconds=60 * 60,
            )
        )  # one hour
    return jobs_list


def create_jobs(name, benchmarks, loops, regex):
    jobs_list = []
    for loop in range(0, loops):
        for bm in benchmarks:
            jobs_list += _collect_bm_data(bm, "opt", name, regex, loop, loops)
    random.shuffle(jobs_list, random.SystemRandom().random)
    return jobs_list


if __name__ == "__main__":
    args = _args()
    jobs_list = create_jobs(
        args.name, args.benchmarks, args.loops, args.regex, args.counters
    )
    jobset.run(jobs_list, maxjobs=args.jobs)