mirror of
https://github.com/facebookresearch/faiss.git
synced 2025-06-03 21:54:02 +08:00
a8118acbc5
Changelog: - changed license: BSD+Patents -> MIT - propagates exceptions raised in sub-indexes of IndexShards and IndexReplicas - support for searching several inverted lists in parallel (parallel_mode != 0) - better support for PQ codes where nbit != 8 or 16 - IVFSpectralHash implementation: spectral hash codes inside an IVF - 6-bit per component scalar quantizer (4 and 8 bit were already supported) - combinations of inverted lists: HStackInvertedLists and VStackInvertedLists - configurable number of threads for OnDiskInvertedLists prefetching (including 0=no prefetch) - more test and demo code compatible with Python 3 (print with parentheses) - refactored benchmark code: data loading is now in a single file
100 lines
2.4 KiB
C++
100 lines
2.4 KiB
C++
/**
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* Copyright (c) Facebook, Inc. and its affiliates.
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*
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* This source code is licensed under the MIT license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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#include <cstdio>
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#include <cstdlib>
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#include <faiss/IndexFlat.h>
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#include <faiss/gpu/GpuAutoTune.h>
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#include <faiss/gpu/GpuIndexFlat.h>
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#include <faiss/gpu/StandardGpuResources.h>
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#include <faiss/gpu/utils/DeviceUtils.h>
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int main() {
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int d = 64; // dimension
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int nb = 100000; // database size
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int nq = 10000; // nb of queries
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float *xb = new float[d * nb];
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float *xq = new float[d * nq];
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for(int i = 0; i < nb; i++) {
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for(int j = 0; j < d; j++)
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xb[d * i + j] = drand48();
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xb[d * i] += i / 1000.;
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}
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for(int i = 0; i < nq; i++) {
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for(int j = 0; j < d; j++)
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xq[d * i + j] = drand48();
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xq[d * i] += i / 1000.;
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}
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int ngpus = faiss::gpu::getNumDevices();
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printf("Number of GPUs: %d\n", ngpus);
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std::vector<faiss::gpu::GpuResources*> res;
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std::vector<int> devs;
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for(int i = 0; i < ngpus; i++) {
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res.push_back(new faiss::gpu::StandardGpuResources);
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devs.push_back(i);
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}
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faiss::IndexFlatL2 cpu_index(d);
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faiss::Index *gpu_index =
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faiss::gpu::index_cpu_to_gpu_multiple(
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res,
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devs,
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&cpu_index
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);
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printf("is_trained = %s\n", gpu_index->is_trained ? "true" : "false");
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gpu_index->add(nb, xb); // add vectors to the index
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printf("ntotal = %ld\n", gpu_index->ntotal);
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int k = 4;
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{ // search xq
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long *I = new long[k * nq];
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float *D = new float[k * nq];
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gpu_index->search(nq, xq, k, D, I);
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// print results
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printf("I (5 first results)=\n");
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for(int i = 0; i < 5; i++) {
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for(int j = 0; j < k; j++)
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printf("%5ld ", I[i * k + j]);
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printf("\n");
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}
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printf("I (5 last results)=\n");
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for(int i = nq - 5; i < nq; i++) {
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for(int j = 0; j < k; j++)
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printf("%5ld ", I[i * k + j]);
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printf("\n");
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}
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delete [] I;
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delete [] D;
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}
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delete gpu_index;
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for(int i = 0; i < ngpus; i++) {
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delete res[i];
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}
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delete [] xb;
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delete [] xq;
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return 0;
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}
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