提交 8970efae 编写于 作者: J Jin Hai 提交者: GitHub

Merge pull request #128 from tinkerlin/upgrade_faiss

Upgrade faiss

Former-commit-id: 0ed5ef40de13008935dbdbe3852e1af47c4d2283
......@@ -14,7 +14,7 @@ container('milvus-build-env') {
sh "export JFROG_ARTFACTORY_URL='${params.JFROG_ARTFACTORY_URL}' \
&& export JFROG_USER_NAME='${USERNAME}' \
&& export JFROG_PASSWORD='${PASSWORD}' \
&& export FAISS_URL='http://192.168.1.105:6060/jinhai/faiss/-/archive/branch-0.2.1/faiss-branch-0.2.1.tar.gz' \
&& export FAISS_URL='http://192.168.1.105:6060/jinhai/faiss/-/archive/branch-0.3.0/faiss-branch-0.3.0.tar.gz' \
&& ./build.sh -t ${params.BUILD_TYPE} -d /opt/milvus -j -u -c"
sh "./coverage.sh -u root -p 123456 -t \$POD_IP"
......
......@@ -14,7 +14,7 @@ container('milvus-build-env') {
sh "export JFROG_ARTFACTORY_URL='${params.JFROG_ARTFACTORY_URL}' \
&& export JFROG_USER_NAME='${USERNAME}' \
&& export JFROG_PASSWORD='${PASSWORD}' \
&& export FAISS_URL='http://192.168.1.105:6060/jinhai/faiss/-/archive/branch-0.2.1/faiss-branch-0.2.1.tar.gz' \
&& export FAISS_URL='http://192.168.1.105:6060/jinhai/faiss/-/archive/branch-0.3.0/faiss-branch-0.3.0.tar.gz' \
&& ./build.sh -t ${params.BUILD_TYPE} -j -d /opt/milvus"
}
}
......
......@@ -18,16 +18,13 @@
#include "db/engine/ExecutionEngineImpl.h"
#include "cache/CpuCacheMgr.h"
#include "cache/GpuCacheMgr.h"
#include "knowhere/common/Config.h"
#include "metrics/Metrics.h"
#include "scheduler/Utils.h"
#include "server/Config.h"
#include "utils/CommonUtil.h"
#include "utils/Exception.h"
#include "utils/Log.h"
#include "knowhere/common/Config.h"
#include "knowhere/common/Exception.h"
#include "knowhere/index/vector_index/IndexIVFSQHybrid.h"
#include "scheduler/Utils.h"
#include "server/Config.h"
#include "wrapper/ConfAdapter.h"
#include "wrapper/ConfAdapterMgr.h"
#include "wrapper/VecImpl.h"
......@@ -260,6 +257,54 @@ ExecutionEngineImpl::Load(bool to_cache) {
Status
ExecutionEngineImpl::CopyToGpu(uint64_t device_id, bool hybrid) {
if (hybrid) {
const std::string key = location_ + ".quantizer";
std::vector<uint64_t> gpus = scheduler::get_gpu_pool();
const int64_t NOT_FOUND = -1;
int64_t device_id = NOT_FOUND;
// cache hit
{
knowhere::QuantizerPtr quantizer = nullptr;
for (auto& gpu : gpus) {
auto cache = cache::GpuCacheMgr::GetInstance(gpu);
if (auto cached_quantizer = cache->GetIndex(key)) {
device_id = gpu;
quantizer = std::static_pointer_cast<CachedQuantizer>(cached_quantizer)->Data();
}
}
if (device_id != NOT_FOUND) {
// cache hit
auto config = std::make_shared<knowhere::QuantizerCfg>();
config->gpu_id = device_id;
config->mode = 2;
auto new_index = index_->LoadData(quantizer, config);
index_ = new_index;
}
}
if (device_id == NOT_FOUND) {
// cache miss
std::vector<int64_t> all_free_mem;
for (auto& gpu : gpus) {
auto cache = cache::GpuCacheMgr::GetInstance(gpu);
auto free_mem = cache->CacheCapacity() - cache->CacheUsage();
all_free_mem.push_back(free_mem);
}
auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end());
auto best_index = std::distance(all_free_mem.begin(), max_e);
device_id = gpus[best_index];
auto pair = index_->CopyToGpuWithQuantizer(device_id);
index_ = pair.first;
// cache
auto cached_quantizer = std::make_shared<CachedQuantizer>(pair.second);
cache::GpuCacheMgr::GetInstance(device_id)->InsertItem(key, cached_quantizer);
}
return Status::OK();
}
......
......@@ -244,11 +244,12 @@ if(CUSTOMIZATION)
# set(FAISS_MD5 "21deb1c708490ca40ecb899122c01403") # commit-id 643e48f479637fd947e7b93fa4ca72b38ecc9a39 branch-0.2.0
# set(FAISS_MD5 "072db398351cca6e88f52d743bbb9fa0") # commit-id 3a2344d04744166af41ef1a74449d68a315bfe17 branch-0.2.1
# set(FAISS_MD5 "c89ea8e655f5cdf58f42486f13614714") # commit-id 9c28a1cbb88f41fa03b03d7204106201ad33276b branch-0.2.1
set(FAISS_MD5 "87fdd86351ffcaf3f80dc26ade63c44b") # commit-id 841a156e67e8e22cd8088e1b58c00afbf2efc30b branch-0.2.1
# set(FAISS_MD5 "87fdd86351ffcaf3f80dc26ade63c44b") # commit-id 841a156e67e8e22cd8088e1b58c00afbf2efc30b branch-0.2.1
set(FAISS_MD5 "f3b2ce3364c3fa7febd3aa7fdd0fe380") # commit-id 694e03458e6b69ce8a62502f71f69a614af5af8f branch-0.3.0
endif()
else()
set(FAISS_SOURCE_URL "https://github.com/facebookresearch/faiss/archive/v1.5.3.tar.gz")
set(FAISS_MD5 "0bc12737b23def156f6a1eb782050135")
set(FAISS_SOURCE_URL "https://github.com/milvus-io/faiss/archive/1.6.0.tar.gz")
set(FAISS_MD5 "eb96d84f98b078a9eec04a796f5c792e")
endif()
message(STATUS "FAISS URL = ${FAISS_SOURCE_URL}")
......
......@@ -38,7 +38,7 @@ class FaissBaseIndex {
virtual void
SealImpl();
protected:
public:
std::shared_ptr<faiss::Index> index_ = nullptr;
};
......
......@@ -15,12 +15,12 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuIndexFlat.h>
#include <memory>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/gpu/GpuIndexIVF.h>
#include <faiss/gpu/GpuIndexIVFFlat.h>
#include <faiss/index_io.h>
#include <memory>
#include "knowhere/adapter/VectorAdapter.h"
#include "knowhere/common/Exception.h"
......@@ -86,7 +86,8 @@ GPUIVF::SerializeImpl() {
faiss::Index* index = index_.get();
faiss::Index* host_index = faiss::gpu::index_gpu_to_cpu(index);
SealImpl();
// TODO(linxj): support seal
// SealImpl();
faiss::write_index(host_index, &writer);
delete host_index;
......@@ -130,13 +131,12 @@ void
GPUIVF::search_impl(int64_t n, const float* data, int64_t k, float* distances, int64_t* labels, const Config& cfg) {
std::lock_guard<std::mutex> lk(mutex_);
// TODO(linxj): gpu index support GenParams
if (auto device_index = std::dynamic_pointer_cast<faiss::gpu::GpuIndexIVF>(index_)) {
auto search_cfg = std::dynamic_pointer_cast<IVFCfg>(cfg);
device_index->setNumProbes(search_cfg->nprobe);
device_index->nprobe = search_cfg->nprobe;
// assert(device_index->getNumProbes() == search_cfg->nprobe);
{
// TODO(linxj): allocate gpu mem
ResScope rs(res_, gpu_id_);
device_index->search(n, (float*)data, k, distances, labels);
}
......
......@@ -16,8 +16,10 @@
// under the License.
#include <faiss/IndexIVFPQ.h>
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/gpu/GpuIndexIVFPQ.h>
#include <faiss/index_factory.h>
#include <memory>
#include "knowhere/adapter/VectorAdapter.h"
......
......@@ -15,9 +15,10 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/index_factory.h>
#include <memory>
#include <utility>
#include "knowhere/adapter/VectorAdapter.h"
#include "knowhere/common/Exception.h"
......@@ -71,13 +72,4 @@ GPUIVFSQ::CopyGpuToCpu(const Config& config) {
return std::make_shared<IVFSQ>(new_index);
}
void
GPUIVFSQ::search_impl(int64_t n, const float* data, int64_t k, float* distances, int64_t* labels, const Config& cfg) {
#ifdef CUSTOMIZATION
GPUIVF::search_impl(n, data, k, distances, labels, cfg);
#else
IVF::search_impl(n, data, k, distances, labels, cfg);
#endif
}
} // namespace knowhere
......@@ -38,10 +38,6 @@ class GPUIVFSQ : public GPUIVF {
VectorIndexPtr
CopyGpuToCpu(const Config& config) override;
protected:
void
search_impl(int64_t n, const float* data, int64_t k, float* distances, int64_t* labels, const Config& cfg) override;
};
} // namespace knowhere
......@@ -15,11 +15,12 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/AutoTune.h>
#include <faiss/IndexFlat.h>
#include <faiss/MetaIndexes.h>
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/index_factory.h>
#include <faiss/index_io.h>
#include <vector>
#include "knowhere/adapter/VectorAdapter.h"
......
......@@ -15,15 +15,12 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/AutoTune.h>
#include <faiss/AuxIndexStructures.h>
#include <faiss/IVFlib.h>
#include <faiss/IndexFlat.h>
#include <faiss/IndexIVF.h>
#include <faiss/IndexIVFFlat.h>
#include <faiss/IndexIVFPQ.h>
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/index_io.h>
#include <faiss/gpu/GpuCloner.h>
#include <chrono>
#include <memory>
#include <utility>
......
......@@ -30,7 +30,7 @@ namespace knowhere {
using Graph = std::vector<std::vector<int64_t>>;
class IVF : public VectorIndex, protected FaissBaseIndex {
class IVF : public VectorIndex, public FaissBaseIndex {
public:
IVF() : FaissBaseIndex(nullptr) {
}
......
......@@ -15,7 +15,8 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/index_factory.h>
#include <memory>
#include "knowhere/adapter/VectorAdapter.h"
......@@ -56,14 +57,7 @@ IVFSQ::CopyCpuToGpu(const int64_t& device_id, const Config& config) {
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(device_id)) {
ResScope rs(res, device_id, false);
#ifdef CUSTOMIZATION
faiss::gpu::GpuClonerOptions option;
option.allInGpu = true;
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), device_id, index_.get(), &option);
#else
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), device_id, index_.get());
#endif
std::shared_ptr<faiss::Index> device_index;
device_index.reset(gpu_index);
......
......@@ -17,19 +17,25 @@
// under the License.
#include "knowhere/index/vector_index/IndexIVFSQHybrid.h"
#include <utility>
#include "faiss/AutoTune.h"
#include "faiss/gpu/GpuAutoTune.h"
#include "faiss/gpu/GpuIndexIVF.h"
#include "knowhere/adapter/VectorAdapter.h"
#include "knowhere/common/Exception.h"
#include <utility>
#include <faiss/gpu/GpuCloner.h>
#include <faiss/gpu/GpuIndexIVF.h>
#include <faiss/index_factory.h>
namespace knowhere {
#ifdef CUSTOMIZATION
// std::mutex g_mutex;
IndexModelPtr
IVFSQHybrid::Train(const DatasetPtr& dataset, const Config& config) {
// std::lock_guard<std::mutex> lk(g_mutex);
auto build_cfg = std::dynamic_pointer_cast<IVFSQCfg>(config);
if (build_cfg != nullptr) {
build_cfg->CheckValid(); // throw exception
......@@ -63,23 +69,25 @@ IVFSQHybrid::Train(const DatasetPtr& dataset, const Config& config) {
VectorIndexPtr
IVFSQHybrid::CopyGpuToCpu(const Config& config) {
if (gpu_mode == 0) {
return std::make_shared<IVFSQHybrid>(index_);
}
std::lock_guard<std::mutex> lk(mutex_);
if (auto device_idx = std::dynamic_pointer_cast<faiss::IndexIVF>(index_)) {
faiss::Index* device_index = index_.get();
faiss::Index* host_index = faiss::gpu::index_gpu_to_cpu(device_index);
faiss::Index* device_index = index_.get();
faiss::Index* host_index = faiss::gpu::index_gpu_to_cpu(device_index);
std::shared_ptr<faiss::Index> new_index;
new_index.reset(host_index);
return std::make_shared<IVFSQHybrid>(new_index);
} else {
// TODO(linxj): why? jinhai
return std::make_shared<IVFSQHybrid>(index_);
}
std::shared_ptr<faiss::Index> new_index;
new_index.reset(host_index);
return std::make_shared<IVFSQHybrid>(new_index);
}
VectorIndexPtr
IVFSQHybrid::CopyCpuToGpu(const int64_t& device_id, const Config& config) {
if (gpu_mode != 0) {
KNOWHERE_THROW_MSG("Not a GpuIndex Type");
}
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(device_id)) {
ResScope rs(res, device_id, false);
faiss::gpu::GpuClonerOptions option;
......@@ -105,16 +113,26 @@ IVFSQHybrid::LoadImpl(const BinarySet& index_binary) {
FaissBaseIndex::LoadImpl(index_binary); // load on cpu
auto* ivf_index = dynamic_cast<faiss::IndexIVF*>(index_.get());
ivf_index->backup_quantizer();
gpu_mode = 0;
}
void
IVFSQHybrid::search_impl(int64_t n, const float* data, int64_t k, float* distances, int64_t* labels,
const Config& cfg) {
// std::lock_guard<std::mutex> lk(g_mutex);
// static int64_t search_count;
// ++search_count;
if (gpu_mode == 2) {
GPUIVF::search_impl(n, data, k, distances, labels, cfg);
} else if (gpu_mode == 1) {
ResScope rs(res_, gpu_id_);
IVF::search_impl(n, data, k, distances, labels, cfg);
// index_->search(n, (float*)data, k, distances, labels);
} else if (gpu_mode == 1) { // hybrid
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(quantizer_gpu_id_)) {
ResScope rs(res, quantizer_gpu_id_, true);
IVF::search_impl(n, data, k, distances, labels, cfg);
} else {
KNOWHERE_THROW_MSG("Hybrid Search Error, can't get gpu: " + std::to_string(quantizer_gpu_id_) + "resource");
}
} else if (gpu_mode == 0) {
IVF::search_impl(n, data, k, distances, labels, cfg);
}
......@@ -122,16 +140,18 @@ IVFSQHybrid::search_impl(int64_t n, const float* data, int64_t k, float* distanc
QuantizerPtr
IVFSQHybrid::LoadQuantizer(const Config& conf) {
// std::lock_guard<std::mutex> lk(g_mutex);
auto quantizer_conf = std::dynamic_pointer_cast<QuantizerCfg>(conf);
if (quantizer_conf != nullptr) {
if (quantizer_conf->mode != 1) {
KNOWHERE_THROW_MSG("mode only support 1 in this func");
}
}
gpu_id_ = quantizer_conf->gpu_id;
auto gpu_id = quantizer_conf->gpu_id;
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(gpu_id_)) {
ResScope rs(res, gpu_id_, false);
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(gpu_id)) {
ResScope rs(res, gpu_id, false);
faiss::gpu::GpuClonerOptions option;
option.allInGpu = true;
......@@ -140,7 +160,7 @@ IVFSQHybrid::LoadQuantizer(const Config& conf) {
index_composition->quantizer = nullptr;
index_composition->mode = quantizer_conf->mode; // only 1
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), gpu_id_, index_composition, &option);
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), gpu_id, index_composition, &option);
delete gpu_index;
auto q = std::make_shared<FaissIVFQuantizer>();
......@@ -148,16 +168,19 @@ IVFSQHybrid::LoadQuantizer(const Config& conf) {
auto& q_ptr = index_composition->quantizer;
q->size = q_ptr->d * q_ptr->getNumVecs() * sizeof(float);
q->quantizer = q_ptr;
q->gpu_id = gpu_id;
res_ = res;
gpu_mode = 1;
return q;
} else {
KNOWHERE_THROW_MSG("CopyCpuToGpu Error, can't get gpu: " + std::to_string(gpu_id_) + "resource");
KNOWHERE_THROW_MSG("CopyCpuToGpu Error, can't get gpu: " + std::to_string(gpu_id) + "resource");
}
}
void
IVFSQHybrid::SetQuantizer(const QuantizerPtr& q) {
// std::lock_guard<std::mutex> lk(g_mutex);
auto ivf_quantizer = std::dynamic_pointer_cast<FaissIVFQuantizer>(q);
if (ivf_quantizer == nullptr) {
KNOWHERE_THROW_MSG("Quantizer type error");
......@@ -170,20 +193,27 @@ IVFSQHybrid::SetQuantizer(const QuantizerPtr& q) {
// delete ivf_index->quantizer;
ivf_index->quantizer = ivf_quantizer->quantizer;
}
quantizer_gpu_id_ = ivf_quantizer->gpu_id;
gpu_mode = 1;
}
void
IVFSQHybrid::UnsetQuantizer() {
// std::lock_guard<std::mutex> lk(g_mutex);
auto* ivf_index = dynamic_cast<faiss::IndexIVF*>(index_.get());
if (ivf_index == nullptr) {
KNOWHERE_THROW_MSG("Index type error");
}
ivf_index->quantizer = nullptr;
quantizer_gpu_id_ = -1;
}
VectorIndexPtr
IVFSQHybrid::LoadData(const knowhere::QuantizerPtr& q, const Config& conf) {
// std::lock_guard<std::mutex> lk(g_mutex);
auto quantizer_conf = std::dynamic_pointer_cast<QuantizerCfg>(conf);
if (quantizer_conf != nullptr) {
if (quantizer_conf->mode != 2) {
......@@ -192,13 +222,11 @@ IVFSQHybrid::LoadData(const knowhere::QuantizerPtr& q, const Config& conf) {
} else {
KNOWHERE_THROW_MSG("conf error");
}
// if (quantizer_conf->gpu_id != gpu_id_) {
// KNOWHERE_THROW_MSG("quantizer and data must on the same gpu card");
// }
gpu_id_ = quantizer_conf->gpu_id;
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(gpu_id_)) {
ResScope rs(res, gpu_id_, false);
auto gpu_id = quantizer_conf->gpu_id;
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(gpu_id)) {
ResScope rs(res, gpu_id, false);
faiss::gpu::GpuClonerOptions option;
option.allInGpu = true;
......@@ -211,18 +239,20 @@ IVFSQHybrid::LoadData(const knowhere::QuantizerPtr& q, const Config& conf) {
index_composition->quantizer = ivf_quantizer->quantizer;
index_composition->mode = quantizer_conf->mode; // only 2
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), gpu_id_, index_composition, &option);
auto gpu_index = faiss::gpu::index_cpu_to_gpu(res->faiss_res.get(), gpu_id, index_composition, &option);
std::shared_ptr<faiss::Index> new_idx;
new_idx.reset(gpu_index);
auto sq_idx = std::make_shared<IVFSQHybrid>(new_idx, gpu_id_, res);
auto sq_idx = std::make_shared<IVFSQHybrid>(new_idx, gpu_id, res);
return sq_idx;
} else {
KNOWHERE_THROW_MSG("CopyCpuToGpu Error, can't get gpu: " + std::to_string(gpu_id_) + "resource");
KNOWHERE_THROW_MSG("CopyCpuToGpu Error, can't get gpu: " + std::to_string(gpu_id) + "resource");
}
}
std::pair<VectorIndexPtr, QuantizerPtr>
IVFSQHybrid::CopyCpuToGpuWithQuantizer(const int64_t& device_id, const Config& config) {
// std::lock_guard<std::mutex> lk(g_mutex);
if (auto res = FaissGpuResourceMgr::GetInstance().GetRes(device_id)) {
ResScope rs(res, device_id, false);
faiss::gpu::GpuClonerOptions option;
......@@ -242,12 +272,29 @@ IVFSQHybrid::CopyCpuToGpuWithQuantizer(const int64_t& device_id, const Config& c
auto q = std::make_shared<FaissIVFQuantizer>();
q->quantizer = index_composition.quantizer;
q->size = index_composition.quantizer->d * index_composition.quantizer->getNumVecs() * sizeof(float);
q->gpu_id = device_id;
return std::make_pair(new_idx, q);
} else {
KNOWHERE_THROW_MSG("CopyCpuToGpu Error, can't get gpu: " + std::to_string(gpu_id_) + "resource");
}
}
void
IVFSQHybrid::set_index_model(IndexModelPtr model) {
std::lock_guard<std::mutex> lk(mutex_);
auto host_index = std::static_pointer_cast<IVFIndexModel>(model);
if (auto gpures = FaissGpuResourceMgr::GetInstance().GetRes(gpu_id_)) {
ResScope rs(gpures, gpu_id_, false);
auto device_index = faiss::gpu::index_cpu_to_gpu(gpures->faiss_res.get(), gpu_id_, host_index->index_.get());
index_.reset(device_index);
res_ = gpures;
gpu_mode = 2;
} else {
KNOWHERE_THROW_MSG("load index model error, can't get gpu_resource");
}
}
FaissIVFQuantizer::~FaissIVFQuantizer() {
if (quantizer != nullptr) {
delete quantizer;
......@@ -307,5 +354,10 @@ IVFSQHybrid::LoadImpl(const BinarySet& index_binary) {
GPUIVF::LoadImpl(index_binary);
}
void
IVFSQHybrid::set_index_model(IndexModelPtr model) {
GPUIVF::set_index_model(model);
}
#endif
} // namespace knowhere
......@@ -17,7 +17,9 @@
#pragma once
#include <faiss/gpu/GpuIndexFlat.h>
#include <faiss/index_io.h>
#include <memory>
#include <utility>
......@@ -29,6 +31,7 @@ namespace knowhere {
#ifdef CUSTOMIZATION
struct FaissIVFQuantizer : public Quantizer {
faiss::gpu::GpuIndexFlat* quantizer = nullptr;
int64_t gpu_id;
~FaissIVFQuantizer() override;
};
......@@ -52,6 +55,9 @@ class IVFSQHybrid : public GPUIVFSQ {
}
public:
void
set_index_model(IndexModelPtr model) override;
QuantizerPtr
LoadQuantizer(const Config& conf);
......@@ -85,6 +91,7 @@ class IVFSQHybrid : public GPUIVFSQ {
protected:
int64_t gpu_mode = 0; // 0,1,2
int64_t quantizer_gpu_id_ = -1;
};
} // namespace knowhere
......@@ -48,6 +48,7 @@ class VectorIndex : public Index {
virtual void
Seal() = 0;
// TODO(linxj): Deprecated
virtual VectorIndexPtr
Clone() = 0;
......
......@@ -17,7 +17,7 @@
#pragma once
#include <faiss/AuxIndexStructures.h>
#include <faiss/impl/io.h>
namespace knowhere {
......
......@@ -3,4 +3,4 @@ BOOST_VERSION=1.70.0
GTEST_VERSION=1.8.1
LAPACK_VERSION=v3.8.0
OPENBLAS_VERSION=v0.3.6
FAISS_VERSION=branch-0.2.1
\ No newline at end of file
FAISS_VERSION=branch-0.3.0
\ No newline at end of file
......@@ -26,7 +26,7 @@
#include "knowhere/index/vector_index/IndexIVFSQ.h"
#include "knowhere/index/vector_index/IndexIVFSQHybrid.h"
constexpr int DEVICEID = 0;
int DEVICEID = 0;
constexpr int64_t DIM = 128;
constexpr int64_t NB = 10000;
constexpr int64_t NQ = 10;
......
......@@ -16,17 +16,23 @@
// under the License.
#include <gtest/gtest.h>
#include <thread>
#include "unittest/Helper.h"
#include "unittest/utils.h"
#include "knowhere/common/Timer.h"
class SingleIndexTest : public DataGen, public TestGpuIndexBase {
protected:
void
SetUp() override {
TestGpuIndexBase::SetUp();
Generate(DIM, NB, NQ);
k = K;
nb = 1000000;
nq = 1000;
dim = DIM;
Generate(dim, nb, nq);
k = 1000;
}
void
......@@ -119,4 +125,113 @@ TEST_F(SingleIndexTest, IVFSQHybrid) {
}
}
// TEST_F(SingleIndexTest, thread_safe) {
// assert(!xb.empty());
//
// index_type = "IVFSQHybrid";
// index_ = IndexFactory(index_type);
// auto base = ParamGenerator::GetInstance().Gen(ParameterType::ivfsq);
// auto conf = std::dynamic_pointer_cast<knowhere::IVFSQCfg>(base);
// conf->nlist = 16384;
// conf->k = k;
// conf->nprobe = 10;
// conf->d = dim;
// auto preprocessor = index_->BuildPreprocessor(base_dataset, conf);
// index_->set_preprocessor(preprocessor);
//
// auto model = index_->Train(base_dataset, conf);
// index_->set_index_model(model);
// index_->Add(base_dataset, conf);
// EXPECT_EQ(index_->Count(), nb);
// EXPECT_EQ(index_->Dimension(), dim);
//
// auto binaryset = index_->Serialize();
//
//
//
// auto cpu_idx = std::make_shared<knowhere::IVFSQHybrid>(DEVICEID);
// cpu_idx->Load(binaryset);
// auto pair = cpu_idx->CopyCpuToGpuWithQuantizer(DEVICEID, conf);
// auto quantizer = pair.second;
//
// auto quantizer_conf = std::make_shared<knowhere::QuantizerCfg>();
// quantizer_conf->mode = 2; // only copy data
// quantizer_conf->gpu_id = DEVICEID;
//
// auto CopyAllToGpu = [&](int64_t search_count, bool do_search = false) {
// for (int i = 0; i < search_count; ++i) {
// auto gpu_idx = cpu_idx->CopyCpuToGpu(DEVICEID, conf);
// if (do_search) {
// auto result = gpu_idx->Search(query_dataset, conf);
// AssertAnns(result, nq, conf->k);
// }
// }
// };
//
// auto hybrid_qt_idx = std::make_shared<knowhere::IVFSQHybrid>(DEVICEID);
// hybrid_qt_idx->Load(binaryset);
// auto SetQuantizerDoSearch = [&](int64_t search_count) {
// for (int i = 0; i < search_count; ++i) {
// hybrid_qt_idx->SetQuantizer(quantizer);
// auto result = hybrid_qt_idx->Search(query_dataset, conf);
// AssertAnns(result, nq, conf->k);
// // PrintResult(result, nq, k);
// hybrid_qt_idx->UnsetQuantizer();
// }
// };
//
// auto hybrid_data_idx = std::make_shared<knowhere::IVFSQHybrid>(DEVICEID);
// hybrid_data_idx->Load(binaryset);
// auto LoadDataDoSearch = [&](int64_t search_count, bool do_search = false) {
// for (int i = 0; i < search_count; ++i) {
// auto hybrid_idx = hybrid_data_idx->LoadData(quantizer, quantizer_conf);
// if (do_search) {
// auto result = hybrid_idx->Search(query_dataset, conf);
//// AssertAnns(result, nq, conf->k);
// }
// }
// };
//
// knowhere::TimeRecorder tc("");
// CopyAllToGpu(2000/2, false);
// tc.RecordSection("CopyAllToGpu witout search");
// CopyAllToGpu(400/2, true);
// tc.RecordSection("CopyAllToGpu with search");
// SetQuantizerDoSearch(6);
// tc.RecordSection("SetQuantizer with search");
// LoadDataDoSearch(2000/2, false);
// tc.RecordSection("LoadData without search");
// LoadDataDoSearch(400/2, true);
// tc.RecordSection("LoadData with search");
//
// {
// std::thread t1(CopyAllToGpu, 2000, false);
// std::thread t2(CopyAllToGpu, 400, true);
// t1.join();
// t2.join();
// }
//
// {
// std::thread t1(SetQuantizerDoSearch, 12);
// std::thread t2(CopyAllToGpu, 400, true);
// t1.join();
// t2.join();
// }
//
// {
// std::thread t1(SetQuantizerDoSearch, 12);
// std::thread t2(LoadDataDoSearch, 400, true);
// t1.join();
// t2.join();
// }
//
// {
// std::thread t1(LoadDataDoSearch, 2000, false);
// std::thread t2(LoadDataDoSearch, 400, true);
// t1.join();
// t2.join();
// }
//
//}
#endif
......@@ -20,19 +20,12 @@
#include <iostream>
#include <thread>
#include <faiss/AutoTune.h>
#include <faiss/gpu/GpuAutoTune.h>
#include <faiss/gpu/GpuIndexIVFFlat.h>
#include "knowhere/common/Exception.h"
#include "knowhere/common/Timer.h"
#include "knowhere/index/vector_index/IndexGPUIVF.h"
#include "knowhere/index/vector_index/IndexGPUIVFPQ.h"
#include "knowhere/index/vector_index/IndexGPUIVFSQ.h"
#include "knowhere/index/vector_index/IndexIVF.h"
#include "knowhere/index/vector_index/IndexIVFPQ.h"
#include "knowhere/index/vector_index/IndexIVFSQ.h"
#include "knowhere/index/vector_index/IndexIVFSQHybrid.h"
#include "knowhere/index/vector_index/helpers/Cloner.h"
#include "unittest/Helper.h"
......@@ -51,6 +44,9 @@ class IVFTest : public DataGen, public TestWithParam<::std::tuple<std::string, P
ParameterType parameter_type;
std::tie(index_type, parameter_type) = GetParam();
// Init_with_default();
// nb = 1000000;
// nq = 1000;
// k = 1000;
Generate(DIM, NB, NQ);
index_ = IndexFactory(index_type);
conf = ParamGenerator::GetInstance().Gen(parameter_type);
......@@ -61,16 +57,6 @@ class IVFTest : public DataGen, public TestWithParam<::std::tuple<std::string, P
knowhere::FaissGpuResourceMgr::GetInstance().Free();
}
knowhere::VectorIndexPtr
ChooseTodo() {
std::vector<std::string> gpu_idx{"GPUIVFSQ"};
auto finder = std::find(gpu_idx.cbegin(), gpu_idx.cend(), index_type);
if (finder != gpu_idx.cend()) {
return knowhere::cloner::CopyCpuToGpu(index_, DEVICEID, knowhere::Config());
}
return index_;
}
protected:
std::string index_type;
knowhere::Config conf;
......@@ -100,8 +86,7 @@ TEST_P(IVFTest, ivf_basic) {
EXPECT_EQ(index_->Count(), nb);
EXPECT_EQ(index_->Dimension(), dim);
auto new_idx = ChooseTodo();
auto result = new_idx->Search(query_dataset, conf);
auto result = index_->Search(query_dataset, conf);
AssertAnns(result, nq, conf->k);
// PrintResult(result, nq, k);
}
......@@ -134,8 +119,7 @@ TEST_P(IVFTest, ivf_serialize) {
index_->set_index_model(model);
index_->Add(base_dataset, conf);
auto new_idx = ChooseTodo();
auto result = new_idx->Search(query_dataset, conf);
auto result = index_->Search(query_dataset, conf);
AssertAnns(result, nq, conf->k);
}
......@@ -159,8 +143,7 @@ TEST_P(IVFTest, ivf_serialize) {
index_->Load(binaryset);
EXPECT_EQ(index_->Count(), nb);
EXPECT_EQ(index_->Dimension(), dim);
auto new_idx = ChooseTodo();
auto result = new_idx->Search(query_dataset, conf);
auto result = index_->Search(query_dataset, conf);
AssertAnns(result, nq, conf->k);
}
}
......@@ -176,8 +159,7 @@ TEST_P(IVFTest, clone_test) {
index_->Add(base_dataset, conf);
EXPECT_EQ(index_->Count(), nb);
EXPECT_EQ(index_->Dimension(), dim);
auto new_idx = ChooseTodo();
auto result = new_idx->Search(query_dataset, conf);
auto result = index_->Search(query_dataset, conf);
AssertAnns(result, nq, conf->k);
// PrintResult(result, nq, k);
......@@ -210,12 +192,6 @@ TEST_P(IVFTest, clone_test) {
// }
// }
{
if (index_type == "IVFSQHybrid") {
return;
}
}
{
// copy from gpu to cpu
std::vector<std::string> support_idx_vec{"GPUIVF", "GPUIVFSQ", "IVFSQHybrid"};
......@@ -277,8 +253,7 @@ TEST_P(IVFTest, gpu_seal_test) {
index_->Add(base_dataset, conf);
EXPECT_EQ(index_->Count(), nb);
EXPECT_EQ(index_->Dimension(), dim);
auto new_idx = ChooseTodo();
auto result = new_idx->Search(query_dataset, conf);
auto result = index_->Search(query_dataset, conf);
AssertAnns(result, nq, conf->k);
auto cpu_idx = knowhere::cloner::CopyGpuToCpu(index_, knowhere::Config());
......
......@@ -94,6 +94,7 @@ class OptimizerInst {
std::lock_guard<std::mutex> lock(mutex_);
if (instance == nullptr) {
std::vector<PassPtr> pass_list;
pass_list.push_back(std::make_shared<LargeSQ8HPass>());
pass_list.push_back(std::make_shared<HybridPass>());
instance = std::make_shared<Optimizer>(pass_list);
}
......
......@@ -26,48 +26,48 @@
namespace milvus {
namespace scheduler {
// bool
// LargeSQ8HPass::Run(const TaskPtr& task) {
// if (task->Type() != TaskType::SearchTask) {
// return false;
// }
//
// auto search_task = std::static_pointer_cast<XSearchTask>(task);
// if (search_task->file_->engine_type_ != (int)engine::EngineType::FAISS_IVFSQ8H) {
// return false;
// }
//
// auto search_job = std::static_pointer_cast<SearchJob>(search_task->job_.lock());
//
// // TODO: future, Index::IVFSQ8H, if nq < threshold set cpu, else set gpu
// if (search_job->nq() < 100) {
// return false;
// }
//
// std::vector<uint64_t> gpus = scheduler::get_gpu_pool();
// std::vector<int64_t> all_free_mem;
// for (auto& gpu : gpus) {
// auto cache = cache::GpuCacheMgr::GetInstance(gpu);
// auto free_mem = cache->CacheCapacity() - cache->CacheUsage();
// all_free_mem.push_back(free_mem);
// }
//
// auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end());
// auto best_index = std::distance(all_free_mem.begin(), max_e);
// auto best_device_id = gpus[best_index];
//
// ResourcePtr res_ptr = ResMgrInst::GetInstance()->GetResource(ResourceType::GPU, best_device_id);
// if (not res_ptr) {
// SERVER_LOG_ERROR << "GpuResource " << best_device_id << " invalid.";
// // TODO: throw critical error and exit
// return false;
// }
//
// auto label = std::make_shared<SpecResLabel>(std::weak_ptr<Resource>(res_ptr));
// task->label() = label;
//
// return true;
// }
bool
LargeSQ8HPass::Run(const TaskPtr& task) {
if (task->Type() != TaskType::SearchTask) {
return false;
}
auto search_task = std::static_pointer_cast<XSearchTask>(task);
if (search_task->file_->engine_type_ != (int)engine::EngineType::FAISS_IVFSQ8H) {
return false;
}
auto search_job = std::static_pointer_cast<SearchJob>(search_task->job_.lock());
// TODO: future, Index::IVFSQ8H, if nq < threshold set cpu, else set gpu
if (search_job->nq() < 100) {
return false;
}
std::vector<uint64_t> gpus = scheduler::get_gpu_pool();
std::vector<int64_t> all_free_mem;
for (auto& gpu : gpus) {
auto cache = cache::GpuCacheMgr::GetInstance(gpu);
auto free_mem = cache->CacheCapacity() - cache->CacheUsage();
all_free_mem.push_back(free_mem);
}
auto max_e = std::max_element(all_free_mem.begin(), all_free_mem.end());
auto best_index = std::distance(all_free_mem.begin(), max_e);
auto best_device_id = gpus[best_index];
ResourcePtr res_ptr = ResMgrInst::GetInstance()->GetResource(ResourceType::GPU, best_device_id);
if (not res_ptr) {
SERVER_LOG_ERROR << "GpuResource " << best_device_id << " invalid.";
// TODO: throw critical error and exit
return false;
}
auto label = std::make_shared<SpecResLabel>(std::weak_ptr<Resource>(res_ptr));
task->label() = label;
return true;
}
} // namespace scheduler
} // namespace milvus
......@@ -37,8 +37,8 @@ class LargeSQ8HPass : public Pass {
LargeSQ8HPass() = default;
public:
// bool
// Run(const TaskPtr& task) override;
bool
Run(const TaskPtr& task) override;
};
using LargeSQ8HPassPtr = std::shared_ptr<LargeSQ8HPass>;
......
......@@ -15,7 +15,7 @@
// specific language governing permissions and limitations
// under the License.
#include <faiss/utils.h>
#include <faiss/utils/distances.h>
#include <omp.h>
#include <cmath>
#include <string>
......
......@@ -71,6 +71,7 @@ class VecIndex : public cache::DataObj {
virtual VecIndexPtr
CopyToCpu(const Config& cfg = Config()) = 0;
// TODO(linxj): Deprecated
virtual VecIndexPtr
Clone() = 0;
......
......@@ -108,7 +108,6 @@ TEST_F(EngineTest, ENGINE_IMPL_TEST) {
ASSERT_EQ(engine_ptr->Dimension(), dimension);
ASSERT_EQ(engine_ptr->Count(), ids.size());
status = engine_ptr->CopyToGpu(0, true);
status = engine_ptr->CopyToGpu(0, false);
//ASSERT_TRUE(status.ok());
......
......@@ -65,7 +65,7 @@ static const char
" cache_insert_data: false # whether load inserted data into cache\n"
"\n"
"engine_config:\n"
" blas_threshold: 20\n"
" use_blas_threshold: 20\n"
"\n"
"resource_config:\n"
" search_resources:\n"
......
......@@ -74,7 +74,7 @@ INSTANTIATE_TEST_CASE_P(WrapperParam, KnowhereWrapperTest,
10,
10),
std::make_tuple(milvus::engine::IndexType::FAISS_IVFSQ8_CPU, "Default", DIM, NB, 10, 10),
// std::make_tuple(milvus::engine::IndexType::FAISS_IVFSQ8_GPU, "Default", DIM, NB, 10, 10),
std::make_tuple(milvus::engine::IndexType::FAISS_IVFSQ8_GPU, "Default", DIM, NB, 10, 10),
std::make_tuple(milvus::engine::IndexType::FAISS_IVFSQ8_MIX, "Default", DIM, NB, 10, 10),
// std::make_tuple(IndexType::NSG_MIX, "Default", 128, 250000, 10, 10),
// std::make_tuple(IndexType::SPTAG_KDT_RNT_CPU, "Default", 128, 250000, 10, 10),
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册