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PerfSelect.cu
/**
* Copyright (c) 2015-present, Facebook, Inc.
* All rights reserved.
*
* This source code is licensed under the BSD+Patents license found in the
* LICENSE file in the root directory of this source tree.
*/
// Copyright 2004-present Facebook. All Rights Reserved.
#include "../utils/DeviceUtils.h"
#include "../utils/BlockSelectKernel.cuh"
#include "../utils/WarpSelectKernel.cuh"
#include "../utils/HostTensor.cuh"
#include "../utils/DeviceTensor.cuh"
#include "../test/TestUtils.h"
#include <algorithm>
#include <gflags/gflags.h>
#include <gtest/gtest.h>
#include <sstream>
#include <unordered_map>
#include <vector>
DEFINE_int32(rows, 10000, "rows in matrix");
DEFINE_int32(cols, 40000, "cols in matrix");
DEFINE_int32(k, 100, "k");
DEFINE_bool(dir, false, "direction of sort");
DEFINE_bool(warp, false, "warp select");
DEFINE_int32(iter, 5, "iterations to run");
DEFINE_bool(k_powers, false, "test k powers of 2 from 1 -> 1024");
int main(int argc, char** argv) {
gflags::ParseCommandLineFlags(&argc, &argv, true);
std::vector<float> v = faiss::gpu::randVecs(FLAGS_rows, FLAGS_cols);
faiss::gpu::HostTensor<float, 2, true> hostVal({FLAGS_rows, FLAGS_cols});
for (int r = 0; r < FLAGS_rows; ++r) {
for (int c = 0; c < FLAGS_cols; ++c) {
hostVal[r][c] = v[r * FLAGS_cols + c];
}
}
// Select top-k on GPU
faiss::gpu::DeviceTensor<float, 2, true> gpuVal(hostVal, 0);
// enough space for any k
faiss::gpu::DeviceTensor<float, 2, true> gpuOutVal({FLAGS_rows, 1024});
faiss::gpu::DeviceTensor<int, 2, true> gpuOutInd({FLAGS_rows, 1024});
int startK = FLAGS_k;
int limitK = FLAGS_k;
if (FLAGS_k_powers) {
startK = 1;
limitK = 1024;
}
for (int k = startK; k <= limitK; k *= 2) {
for (int i = 0; i < FLAGS_iter; ++i) {
if (FLAGS_warp) {
faiss::gpu::runWarpSelect(gpuVal, gpuOutVal, gpuOutInd,
FLAGS_dir, k, 0);
} else {
faiss::gpu::runBlockSelect(gpuVal, gpuOutVal, gpuOutInd,
FLAGS_dir, k, 0);
}
}
}
cudaDeviceSynchronize();
}
faiss::gpu::HostTensor
Definition: HostTensor.cuh:22
faiss::gpu::DeviceTensor< float, 2, true >