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PerfClustering.cpp
1
2 /**
3 * Copyright (c) 2015-present, Facebook, Inc.
4 * All rights reserved.
5 *
6 * This source code is licensed under the CC-by-NC license found in the
7 * LICENSE file in the root directory of this source tree.
8 */
9
10 // Copyright 2004-present Facebook. All Rights Reserved.
11
12 #include "../../utils.h"
13 #include "../../Clustering.h"
14 #include "../GpuIndexFlat.h"
15 #include "../StandardGpuResources.h"
16 #include "IndexWrapper.h"
17 #include "../utils/DeviceUtils.h"
18 #include "../utils/Timer.h"
19 #include <gflags/gflags.h>
20 #include <memory>
21 #include <vector>
22
23 #include <cuda_profiler_api.h>
24
25 DEFINE_int32(num, 10000, "# of vecs");
26 DEFINE_int32(k, 100, "# of clusters");
27 DEFINE_int32(dim, 128, "# of dimensions");
28 DEFINE_int32(niter, 10, "# of iterations");
29 DEFINE_bool(L2_metric, true, "If true, use L2 metric. If false, use IP metric");
30 DEFINE_bool(use_float16, false, "use float16 vectors and math");
31 DEFINE_bool(verbose, false, "turn on clustering logging");
32 DEFINE_int64(seed, -1, "specify random seed");
33 DEFINE_int32(num_gpus, 1, "number of gpus to use");
34 DEFINE_int64(min_paging_size, -1, "minimum size to use CPU -> GPU paged copies");
35 DEFINE_int64(pinned_mem, -1, "pinned memory allocation to use");
36 DEFINE_int32(max_points, -1, "max points per centroid");
37
38 using namespace faiss::gpu;
39
40 int main(int argc, char** argv) {
41 google::ParseCommandLineFlags(&argc, &argv, true);
42
43 cudaProfilerStop();
44
45 auto seed = FLAGS_seed != -1L ? FLAGS_seed : time(nullptr);
46 printf("using seed %ld\n", seed);
47
48 std::vector<float> vecs((size_t) FLAGS_num * FLAGS_dim);
49 faiss::float_rand(vecs.data(), vecs.size(), seed);
50
51 printf("K-means metric %s dim %d centroids %d num train %d niter %d\n",
52 FLAGS_L2_metric ? "L2" : "IP",
53 FLAGS_dim, FLAGS_k, FLAGS_num, FLAGS_niter);
54 printf("float16 math %s\n", FLAGS_use_float16 ? "enabled" : "disabled");
55 printf("verbose %s\n", FLAGS_verbose ? "enabled" : "disabled");
56
57 auto initFn = [](faiss::gpu::GpuResources* res, int dev) ->
58 std::unique_ptr<faiss::gpu::GpuIndexFlat> {
59 if (FLAGS_pinned_mem >= 0) {
60 ((faiss::gpu::StandardGpuResources*) res)->setPinnedMemory(
61 FLAGS_pinned_mem);
62 }
63
64 auto p = std::unique_ptr<faiss::gpu::GpuIndexFlat>(
65 FLAGS_L2_metric ?
66 (faiss::gpu::GpuIndexFlat*)
67 new faiss::gpu::GpuIndexFlatL2(res, dev, FLAGS_dim, FLAGS_use_float16) :
68 (faiss::gpu::GpuIndexFlat*)
69 new faiss::gpu::GpuIndexFlatIP(res, dev, FLAGS_dim, FLAGS_use_float16));
70
71 if (FLAGS_min_paging_size >= 0) {
72 p->setMinPagingSize(FLAGS_min_paging_size);
73 }
74 return p;
75 };
76
77 IndexWrapper<faiss::gpu::GpuIndexFlat> gpuIndex(FLAGS_num_gpus, initFn);
78
79 CUDA_VERIFY(cudaProfilerStart());
80 faiss::gpu::synchronizeAllDevices();
81
82 float gpuTime = 0.0f;
83
84 faiss::ClusteringParameters cp;
85 cp.niter = FLAGS_niter;
86 cp.verbose = FLAGS_verbose;
87
88 if (FLAGS_max_points > 0) {
89 cp.max_points_per_centroid = FLAGS_max_points;
90 }
91
92 faiss::Clustering kmeans(FLAGS_dim, FLAGS_k, cp);
93
94 // Time k-means
95 {
96 CpuTimer timer;
97
98 kmeans.train(FLAGS_num, vecs.data(), *(gpuIndex.getIndex()));
99
100 // There is a device -> host copy above, so no need to time
101 // additional synchronization with the GPU
102 gpuTime = timer.elapsedMilliseconds();
103 }
104
105 CUDA_VERIFY(cudaProfilerStop());
106 printf("k-means time %.3f ms\n", gpuTime);
107
108 CUDA_VERIFY(cudaDeviceSynchronize());
109
110 return 0;
111 }
faiss::gpu::CpuTimer::elapsedMilliseconds
float elapsedMilliseconds()
Returns elapsed time in milliseconds.
Definition: Timer.cpp:53
faiss::ClusteringParameters::niter
int niter
clustering iterations
Definition: Clustering.h:26
faiss::gpu::GpuResources
Definition: GpuResources.h:24
faiss::gpu::CpuTimer
CPU wallclock elapsed timer.
Definition: Timer.h:43
faiss::Clustering
Definition: Clustering.h:58
faiss::gpu::StandardGpuResources
Definition: StandardGpuResources.h:24
faiss::gpu::GpuIndexFlatIP
Definition: GpuIndexFlat.h:158
faiss::gpu::GpuIndexFlatL2
Definition: GpuIndexFlat.h:131
faiss::ClusteringParameters
Definition: Clustering.h:25
faiss::gpu::GpuIndexFlat
Definition: GpuIndexFlat.h:31
faiss::ClusteringParameters::max_points_per_centroid
int max_points_per_centroid
to limit size of dataset
Definition: Clustering.h:35
faiss::gpu::IndexWrapper
Definition: IndexWrapper.h:26