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// Copyright 2021 Google LLC
//
// 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 "sparse_matmul/os/coop_threads.h"
#include <algorithm>
#include <atomic>
#include <numeric>
#include "gtest/gtest.h"
TEST(Threads, LaunchThreads) {
std::atomic<int> counter(0);
auto f = [&](csrblocksparse::SpinBarrier* barrier, int tid) {
counter.fetch_add(tid);
};
const int kNumThreads = 10;
csrblocksparse::LaunchOnThreadsWithBarrier(kNumThreads, f);
ASSERT_EQ(counter.load(), kNumThreads * (kNumThreads - 1) / 2);
}
TEST(Threads, SpinBarrier) {
const int kNumThreads = 10;
std::vector<int> tids(kNumThreads, 0);
std::vector<std::vector<int>> expected;
for (int i = 0; i < 10; ++i) {
expected.emplace_back(kNumThreads);
std::iota(expected.back().begin(), expected.back().end(), 0);
std::transform(expected.back().begin(), expected.back().end(),
expected.back().begin(),
[i](int x) -> int { return (i + 1) * x; });
}
auto f = [&](csrblocksparse::SpinBarrier* barrier, int tid) {
for (int i = 0; i < 10; ++i) {
tids[tid] += tid;
barrier->barrier();
EXPECT_EQ(tids, expected[i]);
barrier->barrier();
}
};
csrblocksparse::LaunchOnThreadsWithBarrier(kNumThreads, f);
}
TEST(Threads, ProducerConsumer) {
constexpr int kNumThreads = 4;
constexpr int kNumIterations = 10;
std::vector<int> shared_data(kNumThreads, 0);
std::vector<std::pair<int, int>> expected;
for (int i = 1; i <= kNumIterations; ++i) {
// Execute the parallel work sequentially.
// Last two threads write their id * iteration.
std::pair<int, int> inputs =
std::make_pair((kNumThreads - 2) * i, (kNumThreads - 1) * i);
// First two threads compute sum and difference of those values.
std::pair<int, int> diffs = std::make_pair(inputs.first + inputs.second,
inputs.first - inputs.second);
// Last two threads compute sum and product.
std::pair<int, int> sums =
std::make_pair(diffs.first + diffs.second, diffs.first * diffs.second);
// First two threads compute product and difference of those values.
expected.emplace_back(
std::make_pair(sums.first * sums.second, sums.first - sums.second));
// Last two threads will check for the correct result.
}
csrblocksparse::ProducerConsumer first_pc(2, 2);
csrblocksparse::ProducerConsumer second_pc(2, 2);
csrblocksparse::ProducerConsumer third_pc(2, 2);
csrblocksparse::ProducerConsumer fourth_pc(2, 2);
auto f = [&](csrblocksparse::SpinBarrier* barrier, int tid) {
for (int i = 1; i <= kNumIterations; ++i) {
if (tid == kNumThreads - 2) {
// Last two threads write their id * iteration.
shared_data[tid] = tid * i;
first_pc.produce();
second_pc.consume();
// They then compute sum and product.
shared_data[tid] = shared_data[0] + shared_data[1];
third_pc.produce();
// They finally check the result.
fourth_pc.consume();
EXPECT_EQ(expected[i - 1].first, shared_data[0]) << "i=" << i;
} else if (tid == kNumThreads - 1) {
shared_data[tid] = tid * i;
first_pc.produce();
second_pc.consume();
shared_data[tid] = shared_data[0] * shared_data[1];
third_pc.produce();
fourth_pc.consume();
EXPECT_EQ(expected[i - 1].second, shared_data[1]) << "i=" << i;
} else if (tid == 0) {
// First two threads compute sum and difference.
first_pc.consume();
shared_data[tid] =
shared_data[kNumThreads - 2] + shared_data[kNumThreads - 1];
second_pc.produce();
// They then compute product and difference.
third_pc.consume();
shared_data[tid] =
shared_data[kNumThreads - 2] * shared_data[kNumThreads - 1];
fourth_pc.produce();
} else if (tid == 1) {
first_pc.consume();
shared_data[tid] =
shared_data[kNumThreads - 2] - shared_data[kNumThreads - 1];
second_pc.produce();
third_pc.consume();
shared_data[tid] =
shared_data[kNumThreads - 2] - shared_data[kNumThreads - 1];
fourth_pc.produce();
}
}
};
csrblocksparse::LaunchOnThreadsWithBarrier(kNumThreads, f);
}
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