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提交 f9930876 编写于 作者: Y yudong.cai
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#89 add faiss benchmark 


Former-commit-id: 768bd53e203b87a1a58ec3f7b618b95937d1ed02
上级 8cb7559d
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core/src/index/unittest/CMakeLists.txt
浏览文件 @ f9930876
...@@ -86,5 +86,6 @@ install(TARGETS test_gpuresource DESTINATION unittest) ...@@ -86,5 +86,6 @@ install(TARGETS test_gpuresource DESTINATION unittest)
install(TARGETS test_customized_index DESTINATION unittest) install(TARGETS test_customized_index DESTINATION unittest)
#add_subdirectory(faiss_ori) #add_subdirectory(faiss_ori)
#add_subdirectory(faiss_benchmark)
add_subdirectory(test_nsg) add_subdirectory(test_nsg)
core/src/index/unittest/faiss_benchmark/CMakeLists.txt 0 → 100644
浏览文件 @ f9930876
include_directories(${INDEX_SOURCE_DIR}/thirdparty)
include_directories(${INDEX_SOURCE_DIR}/include)
include_directories(/usr/local/cuda/include)
include_directories(/usr/local/hdf5/include)
link_directories(/usr/local/cuda/lib64)
link_directories(/usr/local/hdf5/lib)
set(unittest_libs
gtest gmock gtest_main gmock_main)
set(depend_libs
faiss openblas lapack hdf5
arrow ${ARROW_PREFIX}/lib/libjemalloc_pic.a
)
set(basic_libs
cudart cublas
gomp gfortran pthread
)
add_executable(test_faiss_benchmark faiss_benchmark_test.cpp)
target_link_libraries(test_faiss_benchmark ${depend_libs} ${unittest_libs} ${basic_libs})
install(TARGETS test_faiss_benchmark DESTINATION unittest)
core/src/index/unittest/faiss_benchmark/faiss_benchmark_test.cpp 0 → 100644
浏览文件 @ f9930876
// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you 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 <gtest/gtest.h>
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <cassert>
#include <cstring>
#include <faiss/AutoTune.h>
#include <faiss/Index.h>
#include <faiss/IndexIVF.h>
#include <faiss/gpu/StandardGpuResources.h>
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuIndexFlat.h>
#include <faiss/index_io.h>
#include <faiss/utils.h>
#include <hdf5.h>
#include <vector>
#include <sys/stat.h>
#include <sys/time.h>
#include <sys/types.h>
#include <unistd.h>
/*****************************************************
* To run this test, please download the HDF5 from
* https://support.hdfgroup.org/ftp/HDF5/releases/
* and install it to /usr/local/hdf5 .
*****************************************************/
double elapsed() {
struct timeval tv;
gettimeofday(&tv, nullptr);
return tv.tv_sec + tv.tv_usec * 1e-6;
}
void* hdf5_read(const char *file_name,
const char *dataset_name,
H5T_class_t dataset_class,
size_t &d_out,
size_t &n_out) {
hid_t file, dataset, datatype, dataspace, memspace;
H5T_class_t t_class; /* data type class */
H5T_order_t order; /* data order */
size_t size; /* size of the data element stored in file */
hsize_t dimsm[3]; /* memory space dimensions */
hsize_t dims_out[2]; /* dataset dimensions */
hsize_t count[2]; /* size of the hyperslab in the file */
hsize_t offset[2]; /* hyperslab offset in the file */
hsize_t count_out[3]; /* size of the hyperslab in memory */
hsize_t offset_out[3]; /* hyperslab offset in memory */
int rank;
void* data_out; /* output buffer */
/* Open the file and the dataset. */
file = H5Fopen(file_name, H5F_ACC_RDONLY, H5P_DEFAULT);
dataset = H5Dopen2(file, dataset_name, H5P_DEFAULT);
/*
* Get datatype and dataspace handles and then query
* dataset class, order, size, rank and dimensions.
*/
datatype = H5Dget_type(dataset); /* datatype handle */
t_class = H5Tget_class(datatype);
assert(t_class == dataset_class || !"Illegal dataset class type");
order = H5Tget_order(datatype);
switch (order) {
case H5T_ORDER_LE:
printf("Little endian order \n");
break;
case H5T_ORDER_BE:
printf("Big endian order \n");
break;
default:
printf("Illegal endian order \n");
break;
}
size = H5Tget_size(datatype);
printf("Data size is %d \n", (int)size);
dataspace = H5Dget_space(dataset); /* dataspace handle */
rank = H5Sget_simple_extent_ndims(dataspace);
H5Sget_simple_extent_dims(dataspace, dims_out, NULL);
n_out = dims_out[0];
d_out = dims_out[1];
printf("rank %d, dimensions %lu x %lu \n", rank, n_out, d_out);
/* Define hyperslab in the dataset. */
offset[0] = offset[1] = 0;
count[0] = dims_out[0];
count[1] = dims_out[1];
H5Sselect_hyperslab(dataspace, H5S_SELECT_SET, offset, NULL, count, NULL);
/* Define the memory dataspace. */
dimsm[0] = dims_out[0];
dimsm[1] = dims_out[1];
dimsm[2] = 1;
memspace = H5Screate_simple(3, dimsm, NULL);
/* Define memory hyperslab. */
offset_out[0] = offset_out[1] = offset_out[2] = 0;
count_out[0] = dims_out[0];
count_out[1] = dims_out[1];
count_out[2] = 1;
H5Sselect_hyperslab(memspace, H5S_SELECT_SET, offset_out, NULL, count_out, NULL);
/* Read data from hyperslab in the file into the hyperslab in memory and display. */
switch (t_class) {
case H5T_INTEGER:
data_out = new int[dims_out[0] * dims_out[1]];
H5Dread(dataset, H5T_NATIVE_INT, memspace, dataspace, H5P_DEFAULT, data_out);
break;
case H5T_FLOAT:
data_out = new float[dims_out[0] * dims_out[1]];
H5Dread(dataset, H5T_NATIVE_FLOAT, memspace, dataspace, H5P_DEFAULT, data_out);
break;
default:
printf("Illegal dataset class type\n");
break;
}
/* Close/release resources. */
H5Tclose(datatype);
H5Dclose(dataset);
H5Sclose(dataspace);
H5Sclose(memspace);
H5Fclose(file);
return data_out;
}
std::string get_index_file_name(const std::string& ann_test_name,
const std::string& index_key,
int32_t data_loops) {
size_t pos = index_key.find_first_of(',', 0);
std::string file_name = ann_test_name;
file_name = file_name + "_" + index_key.substr(0, pos) + "_" + index_key.substr(pos+1);
file_name = file_name + "_" + std::to_string(data_loops) + ".index";
return file_name;
}
bool parse_ann_test_name(const std::string& ann_test_name,
size_t &dim,
faiss::MetricType &metric_type) {
size_t pos1, pos2;
if (ann_test_name.empty()) return false;
pos1 = ann_test_name.find_first_of('-', 0);
if (pos1 == std::string::npos) return false;
pos2 = ann_test_name.find_first_of('-', pos1 + 1);
if (pos2 == std::string::npos) return false;
dim = std::stoi(ann_test_name.substr(pos1+1, pos2-pos1-1));
std::string metric_str = ann_test_name.substr(pos2+1);
if (metric_str == "angular") {
metric_type = faiss::METRIC_INNER_PRODUCT;
} else if (metric_str == "euclidean") {
metric_type = faiss::METRIC_L2;
} else {
return false;
}
return true;
}
void test_ann_hdf5(const std::string& ann_test_name,
const std::string& index_key,
int32_t index_add_loops,
const std::vector<size_t>& nprobes) {
double t0 = elapsed();
const std::string ann_file_name = ann_test_name + ".hdf5";
faiss::MetricType metric_type;
size_t dim;
if (!parse_ann_test_name(ann_test_name, dim, metric_type)) {
printf("Invalid ann test name: %s\n", ann_test_name.c_str());
return;
}
faiss::Index * index;
size_t d;
std::string index_file_name = get_index_file_name(ann_test_name, index_key, index_add_loops);
try {
index = faiss::read_index(index_file_name.c_str());
d = dim;
}
catch (...) {
printf("Cannot read index file: %s\n", index_file_name.c_str());
printf ("[%.3f s] Loading train set\n", elapsed() - t0);
size_t nb;
float *xb = (float*)hdf5_read(ann_file_name.c_str(), "train", H5T_FLOAT, d, nb);
assert(d == dim || !"dataset does not have correct dimension");
printf ("[%.3f s] Preparing index \"%s\" d=%ld\n",
elapsed() - t0, index_key.c_str(), d);
index = faiss::index_factory(d, index_key.c_str(), metric_type);
printf ("[%.3f s] Training on %ld vectors\n", elapsed() - t0, nb);
index->train(nb, xb);
printf ("[%.3f s] Loading database\n", elapsed() - t0);
// add index multiple times to get ~1G data set
for (int i = 0; i < index_add_loops; i++) {
printf ("[%.3f s] Indexing database, size %ld*%ld\n", elapsed() - t0, nb, d);
index->add(nb, xb);
}
faiss::write_index(index, index_file_name.c_str());
delete [] xb;
}
size_t nq;
float *xq;
{
printf ("[%.3f s] Loading queries\n", elapsed() - t0);
size_t d2;
xq = (float*)hdf5_read(ann_file_name.c_str(), "test", H5T_FLOAT, d2, nq);
assert(d == d2 || !"query does not have same dimension as train set");
}
size_t k; // nb of results per query in the GT
faiss::Index::idx_t *gt; // nq * k matrix of ground-truth nearest-neighbors
{
printf ("[%.3f s] Loading ground truth for %ld queries\n", elapsed() - t0, nq);
// load ground-truth and convert int to long
size_t nq2;
int *gt_int = (int*)hdf5_read(ann_file_name.c_str(), "neighbors", H5T_INTEGER, k, nq2);
assert(nq2 == nq || !"incorrect nb of ground truth entries");
gt = new faiss::Index::idx_t[k * nq];
for(int i = 0; i < k * nq; i++) {
gt[i] = gt_int[i];
}
delete [] gt_int;
}
for (auto nprobe : nprobes) {
faiss::ParameterSpace params;
printf ("[%.3f s] Setting parameter configuration 'nprobe=%lu' on index\n", elapsed() - t0, nprobe);
std::string nprobe_str = "nprobe=" + std::to_string(nprobe);
params.set_index_parameters(index, nprobe_str.c_str());
// output buffers
#if 1
const size_t NQ = 1000, K = 1000;
faiss::Index::idx_t *I = new faiss::Index::idx_t[NQ * K];
float *D = new float[NQ * K];
printf ("\n%s | %s | nprobe=%lu\n", ann_test_name.c_str(), index_key.c_str(), nprobe);
printf ("====================================================\n");
for (size_t t_nq = 10; t_nq <= NQ; t_nq *= 10) { // nq = {10, 100, 1000}
for (size_t t_k = 100; t_k <= K; t_k *= 10) { // k = {100, 1000}
double t_start = elapsed(), t_end;
index->search(t_nq, xq, t_k, D, I);
t_end = elapsed();
// k = 100 for ground truth
int hit = 0;
for (int i = 0; i < t_nq; i++) {
// count the num of results exist in ground truth result set
// consider: each result replicates DATA_LOOPS times
for (int j_c = 0; j_c < k; j_c++) {
int r_c = I[i * t_k + j_c];
for (int j_g = 0; j_g < k/index_add_loops; j_g++) {
if (gt[i * k + j_g] == r_c) {
hit++;
continue;
}
}
}
}
printf("nq = %4ld, k = %4ld, elapse = %fs, R@ = %.4f\n",
t_nq, t_k, (t_end - t_start), (hit / float(t_nq * k / index_add_loops)));
}
}
printf ("====================================================\n");
#else
printf ("[%.3f s] Perform a search on %ld queries\n", elapsed() - t0, nq);
faiss::Index::idx_t *I = new faiss::Index::idx_t[nq * k];
float *D = new float[nq * k];
index->search(nq, xq, k, D, I);
printf ("[%.3f s] Compute recalls\n", elapsed() - t0);
// evaluate result by hand.
int n_1 = 0, n_10 = 0, n_100 = 0;
for(int i = 0; i < nq; i++) {
int gt_nn = gt[i * k];
for(int j = 0; j < k; j++) {
if (I[i * k + j] == gt_nn) {
if(j < 1) n_1++;
if(j < 10) n_10++;
if(j < 100) n_100++;
}
}
}
printf("R@1 = %.4f\n", n_1 / float(nq));
printf("R@10 = %.4f\n", n_10 / float(nq));
printf("R@100 = %.4f\n", n_100 / float(nq));
#endif
printf ("[%.3f s] Search test done\n\n", elapsed() - t0);
delete [] I;
delete [] D;
}
delete [] xq;
delete [] gt;
delete index;
}
#ifdef CUSTOMIZATION
void test_ivfsq8h_gpu(const std::string& ann_test_name,
int32_t index_add_loops,
const std::vector<size_t>& nprobes){
double t0 = elapsed();
const std::string ann_file_name = ann_test_name + ".hdf5";
faiss::MetricType metric_type;
size_t dim;
if (!parse_ann_test_name(ann_test_name, dim, metric_type)) {
printf("Invalid ann test name: %s\n", ann_test_name.c_str());
return;
}
faiss::distance_compute_blas_threshold = 800;
faiss::gpu::StandardGpuResources res;
const std::string index_key = "IVF16384,SQ8Hybrid";
faiss::Index* cpu_index = nullptr;
size_t d;
std::string index_file_name = get_index_file_name(ann_test_name, index_key, index_add_loops);
try{
cpu_index = faiss::read_index(index_file_name.c_str());
d = dim;
}
catch (...){
printf("Cannot read index file: %s\n", index_file_name.c_str());
printf ("[%.3f s] Loading train set\n", elapsed() - t0);
size_t nb;
float *xb = (float*)hdf5_read(ann_file_name.c_str(), "train", H5T_FLOAT, d, nb);
assert(d == dim || !"dataset does not have correct dimension");
printf ("[%.3f s] Preparing index \"%s\" d=%ld\n", elapsed() - t0, index_key.c_str(), d);
faiss::Index *ori_index = faiss::index_factory(d, index_key.c_str(), metric_type);
auto device_index = faiss::gpu::index_cpu_to_gpu(&res, 0, ori_index);
printf ("[%.3f s] Training on %ld vectors\n", elapsed() - t0, nb);
device_index->train(nb, xb);
printf ("[%.3f s] Loading database\n", elapsed() - t0);
for (int i = 0; i < index_add_loops; i++) {
printf ("[%.3f s] Indexing database, size %ld*%ld\n", elapsed() - t0, nb, d);
device_index->add(nb, xb);
}
cpu_index = faiss::gpu::index_gpu_to_cpu(device_index);
faiss::write_index(cpu_index, index_file_name.c_str());
delete []xb;
}
faiss::IndexIVF *cpu_ivf_index = dynamic_cast<faiss::IndexIVF*>(cpu_index);
if(cpu_ivf_index != nullptr) {
cpu_ivf_index->to_readonly();
}
faiss::gpu::GpuClonerOptions option;
option.allInGpu = true;
faiss::IndexComposition index_composition;
index_composition.index = cpu_index;
index_composition.quantizer = nullptr;
index_composition.mode = 1;
auto index = faiss::gpu::index_cpu_to_gpu(&res, 0, &index_composition, &option);
delete index;
size_t nq;
float *xq;
{
printf ("[%.3f s] Loading queries\n", elapsed() - t0);
size_t d2;
xq = (float*)hdf5_read(ann_file_name.c_str(), "test", H5T_FLOAT, d2, nq);
assert(d == d2 || !"query does not have same dimension as train set");
}
size_t k;
faiss::Index::idx_t *gt;
{
printf ("[%.3f s] Loading ground truth for %ld queries\n", elapsed() - t0, nq);
size_t nq2;
int *gt_int = (int*)hdf5_read(ann_file_name.c_str(), "neighbors", H5T_INTEGER, k, nq2);
assert(nq2 == nq || !"incorrect nb of ground truth entries");
gt = new faiss::Index::idx_t[k * nq];
for (unsigned long i = 0; i < k * nq; ++i) {
gt[i] = gt_int[i];
}
delete []gt_int;
}
for (auto nprobe : nprobes){
printf ("[%.3f s] Setting parameter configuration 'nprobe=%lu' on index\n",
elapsed() - t0, nprobe);
auto ivf_index = dynamic_cast<faiss::IndexIVF *>(cpu_index);
ivf_index->nprobe = nprobe;
auto is_gpu_flat_index = dynamic_cast<faiss::gpu::GpuIndexFlat*>(ivf_index->quantizer);
if(is_gpu_flat_index == nullptr) {
delete ivf_index->quantizer;
ivf_index->quantizer = index_composition.quantizer;
}
const size_t NQ = 1000, K = 1000;
long *I = new faiss::Index::idx_t[NQ * K];
float *D = new float[NQ * K];
printf ("\n%s %ld\n", index_key.c_str(), nprobe);
printf ("\n%s | %s | nprobe=%lu\n", ann_test_name.c_str(), index_key.c_str(), nprobe);
printf ("====================================================\n");
for (size_t t_nq = 10; t_nq <= NQ; t_nq *= 10) { // nq = {10, 100, 1000}
for (size_t t_k = 100; t_k <= K; t_k *= 10) { // k = {100, 1000}
double t_start = elapsed(), t_end;
cpu_index->search(t_nq, xq, t_k, D, I);
t_end = elapsed();
// k = 100 for ground truth
int hit = 0;
for (unsigned long i = 0; i < t_nq; i++) {
// count the num of results exist in ground truth result set
// consider: each result replicates DATA_LOOPS times
for (unsigned long j_c = 0; j_c < k; j_c++) {
int r_c = I[i * t_k + j_c];
for (unsigned long j_g = 0; j_g < k/index_add_loops; j_g++) {
if (gt[i * k + j_g] == r_c) {
hit++;
continue;
}
}
}
}
printf("nq = %4ld, k = %4ld, elapse = %fs, R@ = %.4f\n",
t_nq, t_k, (t_end - t_start), (hit / float(t_nq * k / index_add_loops)));
}
}
printf ("====================================================\n");
printf ("[%.3f s] Search test done\n\n", elapsed() - t0);
delete [] I;
delete [] D;
}
delete [] xq;
delete [] gt;
delete cpu_index;
}
#endif
/************************************************************************************
* https://github.com/erikbern/ann-benchmarks
*
* Dataset Dimensions Train_size Test_size Neighbors Distance Download
* Fashion-
* MNIST 784 60,000 10,000 100 Euclidean HDF5 (217MB)
* GIST 960 1,000,000 1,000 100 Euclidean HDF5 (3.6GB)
* GloVe 100 1,183,514 10,000 100 Angular HDF5 (463MB)
* GloVe 200 1,183,514 10,000 100 Angular HDF5 (918MB)
* MNIST 784 60,000 10,000 100 Euclidean HDF5 (217MB)
* NYTimes 256 290,000 10,000 100 Angular HDF5 (301MB)
* SIFT 128 1,000,000 10,000 100 Euclidean HDF5 (501MB)
*************************************************************************************/
TEST(FAISSTEST, sift1m_L2) {
test_ann_hdf5("sift-128-euclidean", "IVF4096,Flat", 2, {8, 128});
test_ann_hdf5("sift-128-euclidean", "IVF16384,SQ8", 2, {8, 128});
test_ann_hdf5("sift-128-euclidean", "IVF16384,SQ8Hybrid", 2, {8, 128});
#ifdef CUSTOMIZATION
test_ivfsq8h_gpu("sift-128-euclidean", 2, {8, 128});
#endif
test_ann_hdf5("glove-200-angular", "IVF4096,Flat", 1, {8, 128});
test_ann_hdf5("glove-200-angular", "IVF16384,SQ8", 1, {8, 128});
test_ann_hdf5("glove-200-angular", "IVF16384,SQ8Hybrid", 1, {8, 128});
#ifdef CUSTOMIZATION
test_ivfsq8h_gpu("glove-200-angular", 2, {128, 1024});
#endif
}
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