foundationdb/flowbench/BenchNet2.actor.cpp

94 lines
3.1 KiB
C++

/*
* BenchNet2.actor.cpp
*
* This source file is part of the FoundationDB open source project
*
* Copyright 2013-2022 Apple Inc. and the FoundationDB project 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.
*/
#include "benchmark/benchmark.h"
#include "flow/IRandom.h"
#include "flow/flow.h"
#include "flow/DeterministicRandom.h"
#include "flow/network.h"
#include "flow/ThreadHelper.actor.h"
#include "flow/actorcompiler.h" // This must be the last #include.
ACTOR static Future<Void> increment(TaskPriority priority, uint32_t* sum) {
wait(delay(0, priority));
++(*sum);
return Void();
}
static inline TaskPriority getRandomTaskPriority(DeterministicRandom& rand) {
return static_cast<TaskPriority>(rand.randomInt(0, 100));
}
ACTOR static Future<Void> benchNet2Actor(benchmark::State* benchState) {
state size_t actorCount = benchState->range(0);
state uint32_t sum;
state int seed = platform::getRandomSeed();
while (benchState->KeepRunning()) {
sum = 0;
std::vector<Future<Void>> futures;
futures.reserve(actorCount);
DeterministicRandom rand(seed);
for (int i = 0; i < actorCount; ++i) {
futures.push_back(increment(getRandomTaskPriority(rand), &sum));
}
wait(waitForAll(futures));
benchmark::DoNotOptimize(sum);
}
benchState->SetItemsProcessed(actorCount * static_cast<long>(benchState->iterations()));
return Void();
}
static void bench_net2(benchmark::State& benchState) {
onMainThread([&benchState] { return benchNet2Actor(&benchState); }).blockUntilReady();
}
BENCHMARK(bench_net2)->Range(1, 1 << 16)->ReportAggregatesOnly(true);
static constexpr bool DELAY = false;
static constexpr bool YIELD = true;
ACTOR template <bool useYield>
static Future<Void> benchDelay(benchmark::State* benchState) {
// Number of random delays to start to just to populate the run loop
// priority queue
state int64_t timerCount = benchState->range(0);
state std::vector<Future<Void>> futures;
state DeterministicRandom rand(platform::getRandomSeed());
while (--timerCount > 0) {
futures.push_back(delay(1.0 + rand.random01(), getRandomTaskPriority(rand)));
}
while (benchState->KeepRunning()) {
wait(useYield ? yield() : delay(0));
}
benchState->SetItemsProcessed(static_cast<long>(benchState->iterations()));
return Void();
}
template <bool useYield>
static void bench_delay(benchmark::State& benchState) {
onMainThread([&benchState] { return benchDelay<useYield>(&benchState); }).blockUntilReady();
}
BENCHMARK_TEMPLATE(bench_delay, DELAY)->Range(0, 1 << 16)->ReportAggregatesOnly(true);
BENCHMARK_TEMPLATE(bench_delay, YIELD)->Range(0, 1 << 16)->ReportAggregatesOnly(true);