152 lines
4.8 KiB
Plaintext
152 lines
4.8 KiB
Plaintext
/**
|
|
* 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.
|
|
*/
|
|
|
|
|
|
#include "../../IndexIVFFlat.h"
|
|
#include "../../index_io.h"
|
|
#include "../../utils.h"
|
|
|
|
#include "../GpuIndexIVFFlat.h"
|
|
#include "IndexWrapper.h"
|
|
#include "../test/TestUtils.h"
|
|
#include "../utils/DeviceTensor.cuh"
|
|
#include "../utils/DeviceUtils.h"
|
|
#include "../utils/HostTensor.cuh"
|
|
#include "../utils/Timer.h"
|
|
#include <gflags/gflags.h>
|
|
#include <map>
|
|
#include <memory>
|
|
#include <vector>
|
|
|
|
#include <cuda_profiler_api.h>
|
|
|
|
DEFINE_int32(nprobe, 5, "number of coarse centroids to probe");
|
|
DEFINE_int32(k, 3, "final number of closest results returned");
|
|
DEFINE_int32(num_queries, 3, "number of query vectors");
|
|
DEFINE_string(in, "/home/jhj/local/index.out", "index file for input");
|
|
DEFINE_bool(diff, true, "show exact distance + index output discrepancies");
|
|
DEFINE_bool(use_float16, false, "use encodings in float16");
|
|
DEFINE_bool(use_float16_coarse, false, "coarse quantizer in float16");
|
|
DEFINE_int64(seed, -1, "specify random seed");
|
|
DEFINE_int32(num_gpus, 1, "number of gpus to use");
|
|
DEFINE_int32(index, 2, "0 = no indices on GPU; 1 = 32 bit, 2 = 64 bit on GPU");
|
|
|
|
using namespace faiss::gpu;
|
|
|
|
int main(int argc, char** argv) {
|
|
gflags::ParseCommandLineFlags(&argc, &argv, true);
|
|
|
|
cudaProfilerStop();
|
|
|
|
auto seed = FLAGS_seed != -1L ? FLAGS_seed : time(nullptr);
|
|
printf("using seed %ld\n", seed);
|
|
|
|
auto numQueries = FLAGS_num_queries;
|
|
|
|
auto index = std::unique_ptr<faiss::IndexIVFFlat>(
|
|
dynamic_cast<faiss::IndexIVFFlat*>(faiss::read_index(FLAGS_in.c_str())));
|
|
FAISS_ASSERT((bool) index);
|
|
index->nprobe = FLAGS_nprobe;
|
|
|
|
auto dim = index->d;
|
|
|
|
printf("Database: dim %d num vecs %ld\n", dim, index->ntotal);
|
|
printf("Coarse centroids: %ld\n", index->quantizer->ntotal);
|
|
printf("L2 lookup: %d queries, nprobe %d, total k %d\n",
|
|
numQueries, FLAGS_nprobe, FLAGS_k);
|
|
printf("float16 coarse quantizer %s\n",
|
|
FLAGS_use_float16_coarse ? "enabled" : "disabled");
|
|
printf("float16 encoding %s\n",
|
|
FLAGS_use_float16 ? "enabled" : "disabled");
|
|
|
|
// Convert to GPU index
|
|
printf("Copying index to %d GPU(s)...\n", FLAGS_num_gpus);
|
|
|
|
auto initFn = [&index](faiss::gpu::GpuResources* res, int dev) ->
|
|
std::unique_ptr<faiss::gpu::GpuIndexIVFFlat> {
|
|
GpuIndexIVFFlatConfig config;
|
|
config.device = dev;
|
|
config.indicesOptions = (faiss::gpu::IndicesOptions) FLAGS_index;
|
|
config.flatConfig.useFloat16 = FLAGS_use_float16_coarse;
|
|
config.useFloat16IVFStorage = FLAGS_use_float16;
|
|
|
|
auto p = std::unique_ptr<faiss::gpu::GpuIndexIVFFlat>(
|
|
new faiss::gpu::GpuIndexIVFFlat(res,
|
|
index->d,
|
|
index->nlist,
|
|
index->metric_type,
|
|
config));
|
|
p->copyFrom(index.get());
|
|
return p;
|
|
};
|
|
|
|
IndexWrapper<faiss::gpu::GpuIndexIVFFlat> gpuIndex(FLAGS_num_gpus, initFn);
|
|
gpuIndex.setNumProbes(FLAGS_nprobe);
|
|
printf("copy done\n");
|
|
|
|
// Build query vectors
|
|
HostTensor<float, 2, true> cpuQuery({numQueries, dim});
|
|
faiss::float_rand(cpuQuery.data(), cpuQuery.numElements(), seed);
|
|
|
|
// Time faiss CPU
|
|
HostTensor<float, 2, true> cpuDistances({numQueries, FLAGS_k});
|
|
HostTensor<faiss::Index::idx_t, 2, true> cpuIndices({numQueries, FLAGS_k});
|
|
|
|
float cpuTime = 0.0f;
|
|
|
|
{
|
|
CpuTimer timer;
|
|
index->search(numQueries,
|
|
cpuQuery.data(),
|
|
FLAGS_k,
|
|
cpuDistances.data(),
|
|
cpuIndices.data());
|
|
|
|
cpuTime = timer.elapsedMilliseconds();
|
|
}
|
|
|
|
printf("CPU time %.3f ms\n", cpuTime);
|
|
|
|
HostTensor<float, 2, true> gpuDistances({numQueries, FLAGS_k});
|
|
HostTensor<faiss::Index::idx_t, 2, true> gpuIndices({numQueries, FLAGS_k});
|
|
|
|
CUDA_VERIFY(cudaProfilerStart());
|
|
faiss::gpu::synchronizeAllDevices();
|
|
|
|
float gpuTime = 0.0f;
|
|
|
|
// Time GPU
|
|
{
|
|
CpuTimer timer;
|
|
|
|
gpuIndex.getIndex()->search(cpuQuery.getSize(0),
|
|
cpuQuery.data(),
|
|
FLAGS_k,
|
|
gpuDistances.data(),
|
|
gpuIndices.data());
|
|
|
|
// There is a device -> host copy above, so no need to time
|
|
// additional synchronization with the GPU
|
|
gpuTime = timer.elapsedMilliseconds();
|
|
}
|
|
|
|
CUDA_VERIFY(cudaProfilerStop());
|
|
printf("GPU time %.3f ms\n", gpuTime);
|
|
|
|
compareLists(cpuDistances.data(), cpuIndices.data(),
|
|
gpuDistances.data(), gpuIndices.data(),
|
|
numQueries, FLAGS_k,
|
|
"", true, FLAGS_diff, false);
|
|
|
|
CUDA_VERIFY(cudaDeviceSynchronize());
|
|
// printf("\ncudaMalloc usage %zd\n",
|
|
// resources.getMemoryManager().getHighWaterCudaMalloc());
|
|
|
|
return 0;
|
|
}
|