milvus/core/src/db/engine/ExecutionEngineImpl.cpp
Jin Hai e1027e9e65
#1240 Update license declaration of each file (#1241)
* #1240 Update license declaration of each files

Signed-off-by: jinhai <hai.jin@zilliz.com>

* #1240 Update CHANGELOG

Signed-off-by: jinhai <hai.jin@zilliz.com>
2020-02-17 23:40:58 +08:00

776 lines
25 KiB
C++

// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed 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 "db/engine/ExecutionEngineImpl.h"
#include <fiu-local.h>
#include <stdexcept>
#include <utility>
#include <vector>
#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 "utils/ValidationUtil.h"
#include "wrapper/BinVecImpl.h"
#include "wrapper/ConfAdapter.h"
#include "wrapper/ConfAdapterMgr.h"
#include "wrapper/VecImpl.h"
#include "wrapper/VecIndex.h"
//#define ON_SEARCH
namespace milvus {
namespace engine {
namespace {
Status
MappingMetricType(MetricType metric_type, knowhere::METRICTYPE& kw_type) {
switch (metric_type) {
case MetricType::IP:
kw_type = knowhere::METRICTYPE::IP;
break;
case MetricType::L2:
kw_type = knowhere::METRICTYPE::L2;
break;
case MetricType::HAMMING:
kw_type = knowhere::METRICTYPE::HAMMING;
break;
case MetricType::JACCARD:
kw_type = knowhere::METRICTYPE::JACCARD;
break;
case MetricType::TANIMOTO:
kw_type = knowhere::METRICTYPE::TANIMOTO;
break;
default:
return Status(DB_ERROR, "Unsupported metric type");
}
return Status::OK();
}
bool
IsBinaryIndexType(IndexType type) {
return type == IndexType::FAISS_BIN_IDMAP || type == IndexType::FAISS_BIN_IVFLAT_CPU;
}
} // namespace
class CachedQuantizer : public cache::DataObj {
public:
explicit CachedQuantizer(knowhere::QuantizerPtr data) : data_(std::move(data)) {
}
knowhere::QuantizerPtr
Data() {
return data_;
}
int64_t
Size() override {
return data_->size;
}
private:
knowhere::QuantizerPtr data_;
};
ExecutionEngineImpl::ExecutionEngineImpl(uint16_t dimension, const std::string& location, EngineType index_type,
MetricType metric_type, int32_t nlist)
: location_(location), dim_(dimension), index_type_(index_type), metric_type_(metric_type), nlist_(nlist) {
EngineType tmp_index_type = server::ValidationUtil::IsBinaryMetricType((int32_t)metric_type)
? EngineType::FAISS_BIN_IDMAP
: EngineType::FAISS_IDMAP;
index_ = CreatetVecIndex(tmp_index_type);
if (!index_) {
throw Exception(DB_ERROR, "Unsupported index type");
}
TempMetaConf temp_conf;
temp_conf.gpu_id = gpu_num_;
temp_conf.dim = dimension;
auto status = MappingMetricType(metric_type, temp_conf.metric_type);
if (!status.ok()) {
throw Exception(DB_ERROR, status.message());
}
auto adapter = AdapterMgr::GetInstance().GetAdapter(index_->GetType());
auto conf = adapter->Match(temp_conf);
ErrorCode ec = KNOWHERE_UNEXPECTED_ERROR;
if (auto bf_index = std::dynamic_pointer_cast<BFIndex>(index_)) {
ec = bf_index->Build(conf);
} else if (auto bf_bin_index = std::dynamic_pointer_cast<BinBFIndex>(index_)) {
ec = bf_bin_index->Build(conf);
}
if (ec != KNOWHERE_SUCCESS) {
throw Exception(DB_ERROR, "Build index error");
}
}
ExecutionEngineImpl::ExecutionEngineImpl(VecIndexPtr index, const std::string& location, EngineType index_type,
MetricType metric_type, int32_t nlist)
: index_(std::move(index)), location_(location), index_type_(index_type), metric_type_(metric_type), nlist_(nlist) {
}
VecIndexPtr
ExecutionEngineImpl::CreatetVecIndex(EngineType type) {
#ifdef MILVUS_GPU_VERSION
server::Config& config = server::Config::GetInstance();
bool gpu_resource_enable = true;
config.GetGpuResourceConfigEnable(gpu_resource_enable);
fiu_do_on("ExecutionEngineImpl.CreatetVecIndex.gpu_res_disabled", gpu_resource_enable = false);
#endif
fiu_do_on("ExecutionEngineImpl.CreatetVecIndex.invalid_type", type = EngineType::INVALID);
std::shared_ptr<VecIndex> index;
switch (type) {
case EngineType::FAISS_IDMAP: {
index = GetVecIndexFactory(IndexType::FAISS_IDMAP);
break;
}
case EngineType::FAISS_IVFFLAT: {
#ifdef MILVUS_GPU_VERSION
if (gpu_resource_enable)
index = GetVecIndexFactory(IndexType::FAISS_IVFFLAT_MIX);
else
#endif
index = GetVecIndexFactory(IndexType::FAISS_IVFFLAT_CPU);
break;
}
case EngineType::FAISS_IVFSQ8: {
#ifdef MILVUS_GPU_VERSION
if (gpu_resource_enable)
index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_MIX);
else
#endif
index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_CPU);
break;
}
case EngineType::NSG_MIX: {
index = GetVecIndexFactory(IndexType::NSG_MIX);
break;
}
#ifdef CUSTOMIZATION
#ifdef MILVUS_GPU_VERSION
case EngineType::FAISS_IVFSQ8H: {
if (gpu_resource_enable) {
index = GetVecIndexFactory(IndexType::FAISS_IVFSQ8_HYBRID);
} else {
throw Exception(DB_ERROR, "No GPU resources for IVFSQ8H");
}
break;
}
#endif
#endif
case EngineType::FAISS_PQ: {
#ifdef MILVUS_GPU_VERSION
if (gpu_resource_enable)
index = GetVecIndexFactory(IndexType::FAISS_IVFPQ_MIX);
else
#endif
index = GetVecIndexFactory(IndexType::FAISS_IVFPQ_CPU);
break;
}
case EngineType::SPTAG_KDT: {
index = GetVecIndexFactory(IndexType::SPTAG_KDT_RNT_CPU);
break;
}
case EngineType::SPTAG_BKT: {
index = GetVecIndexFactory(IndexType::SPTAG_BKT_RNT_CPU);
break;
}
case EngineType::HNSW: {
index = GetVecIndexFactory(IndexType::HNSW);
break;
}
case EngineType::FAISS_BIN_IDMAP: {
index = GetVecIndexFactory(IndexType::FAISS_BIN_IDMAP);
break;
}
case EngineType::FAISS_BIN_IVFFLAT: {
index = GetVecIndexFactory(IndexType::FAISS_BIN_IVFLAT_CPU);
break;
}
default: {
ENGINE_LOG_ERROR << "Unsupported index type";
return nullptr;
}
}
return index;
}
void
ExecutionEngineImpl::HybridLoad() const {
if (index_type_ != EngineType::FAISS_IVFSQ8H) {
return;
}
if (index_->GetType() == IndexType::FAISS_IDMAP) {
ENGINE_LOG_WARNING << "HybridLoad with type FAISS_IDMAP, ignore";
return;
}
#ifdef MILVUS_GPU_VERSION
const std::string key = location_ + ".quantizer";
server::Config& config = server::Config::GetInstance();
std::vector<int64_t> gpus;
Status s = config.GetGpuResourceConfigSearchResources(gpus);
if (!s.ok()) {
ENGINE_LOG_ERROR << s.message();
return;
}
// cache hit
{
const int64_t NOT_FOUND = -1;
int64_t device_id = NOT_FOUND;
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) {
index_->SetQuantizer(quantizer);
return;
}
}
// 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);
auto best_device_id = gpus[best_index];
auto quantizer_conf = std::make_shared<knowhere::QuantizerCfg>();
quantizer_conf->mode = 1;
quantizer_conf->gpu_id = best_device_id;
auto quantizer = index_->LoadQuantizer(quantizer_conf);
if (quantizer == nullptr) {
ENGINE_LOG_ERROR << "quantizer is nullptr";
}
index_->SetQuantizer(quantizer);
auto cache_quantizer = std::make_shared<CachedQuantizer>(quantizer);
cache::GpuCacheMgr::GetInstance(best_device_id)->InsertItem(key, cache_quantizer);
}
#endif
}
void
ExecutionEngineImpl::HybridUnset() const {
if (index_type_ != EngineType::FAISS_IVFSQ8H) {
return;
}
if (index_->GetType() == IndexType::FAISS_IDMAP) {
return;
}
index_->UnsetQuantizer();
}
Status
ExecutionEngineImpl::AddWithIds(int64_t n, const float* xdata, const int64_t* xids) {
auto status = index_->Add(n, xdata, xids);
return status;
}
Status
ExecutionEngineImpl::AddWithIds(int64_t n, const uint8_t* xdata, const int64_t* xids) {
auto status = index_->Add(n, xdata, xids);
return status;
}
size_t
ExecutionEngineImpl::Count() const {
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, return count 0";
return 0;
}
return index_->Count();
}
size_t
ExecutionEngineImpl::Size() const {
if (IsBinaryIndexType(index_->GetType())) {
return (size_t)(Count() * Dimension() / 8);
} else {
return (size_t)(Count() * Dimension()) * sizeof(float);
}
}
size_t
ExecutionEngineImpl::Dimension() const {
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, return dimension " << dim_;
return dim_;
}
return index_->Dimension();
}
size_t
ExecutionEngineImpl::PhysicalSize() const {
return server::CommonUtil::GetFileSize(location_);
}
Status
ExecutionEngineImpl::Serialize() {
auto status = write_index(index_, location_);
// here we reset index size by file size,
// since some index type(such as SQ8) data size become smaller after serialized
index_->set_size(PhysicalSize());
ENGINE_LOG_DEBUG << "Finish serialize index file: " << location_ << " size: " << index_->Size();
if (index_->Size() == 0) {
std::string msg = "Failed to serialize file: " + location_ + " reason: out of disk space or memory";
status = Status(DB_ERROR, msg);
}
return status;
}
Status
ExecutionEngineImpl::Load(bool to_cache) {
index_ = std::static_pointer_cast<VecIndex>(cache::CpuCacheMgr::GetInstance()->GetIndex(location_));
bool already_in_cache = (index_ != nullptr);
if (!already_in_cache) {
try {
double physical_size = PhysicalSize();
server::CollectExecutionEngineMetrics metrics(physical_size);
index_ = read_index(location_);
if (index_ == nullptr) {
std::string msg = "Failed to load index from " + location_;
ENGINE_LOG_ERROR << msg;
return Status(DB_ERROR, msg);
} else {
ENGINE_LOG_DEBUG << "Disk io from: " << location_;
}
} catch (std::exception& e) {
ENGINE_LOG_ERROR << e.what();
return Status(DB_ERROR, e.what());
}
}
if (!already_in_cache && to_cache) {
Cache();
}
return Status::OK();
}
Status
ExecutionEngineImpl::CopyToGpu(uint64_t device_id, bool hybrid) {
#if 0
if (hybrid) {
const std::string key = location_ + ".quantizer";
std::vector<uint64_t> gpus{device_id};
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();
}
#endif
#ifdef MILVUS_GPU_VERSION
auto index = std::static_pointer_cast<VecIndex>(cache::GpuCacheMgr::GetInstance(device_id)->GetIndex(location_));
bool already_in_cache = (index != nullptr);
if (already_in_cache) {
index_ = index;
} else {
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to copy to gpu";
return Status(DB_ERROR, "index is null");
}
try {
index_ = index_->CopyToGpu(device_id);
ENGINE_LOG_DEBUG << "CPU to GPU" << device_id;
} catch (std::exception& e) {
ENGINE_LOG_ERROR << e.what();
return Status(DB_ERROR, e.what());
}
}
if (!already_in_cache) {
GpuCache(device_id);
}
#endif
return Status::OK();
}
Status
ExecutionEngineImpl::CopyToIndexFileToGpu(uint64_t device_id) {
#ifdef MILVUS_GPU_VERSION
// the ToIndexData is only a placeholder, cpu-copy-to-gpu action is performed in
gpu_num_ = device_id;
auto to_index_data = std::make_shared<ToIndexData>(PhysicalSize());
cache::DataObjPtr obj = std::static_pointer_cast<cache::DataObj>(to_index_data);
milvus::cache::GpuCacheMgr::GetInstance(device_id)->InsertItem(location_ + "_placeholder", obj);
#endif
return Status::OK();
}
Status
ExecutionEngineImpl::CopyToCpu() {
auto index = std::static_pointer_cast<VecIndex>(cache::CpuCacheMgr::GetInstance()->GetIndex(location_));
bool already_in_cache = (index != nullptr);
if (already_in_cache) {
index_ = index;
} else {
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to copy to cpu";
return Status(DB_ERROR, "index is null");
}
try {
index_ = index_->CopyToCpu();
ENGINE_LOG_DEBUG << "GPU to CPU";
} catch (std::exception& e) {
ENGINE_LOG_ERROR << e.what();
return Status(DB_ERROR, e.what());
}
}
if (!already_in_cache) {
Cache();
}
return Status::OK();
}
// ExecutionEnginePtr
// ExecutionEngineImpl::Clone() {
// if (index_ == nullptr) {
// ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to clone";
// return nullptr;
// }
//
// auto ret = std::make_shared<ExecutionEngineImpl>(dim_, location_, index_type_, metric_type_, nlist_);
// ret->Init();
// ret->index_ = index_->Clone();
// return ret;
//}
Status
ExecutionEngineImpl::Merge(const std::string& location) {
if (location == location_) {
return Status(DB_ERROR, "Cannot Merge Self");
}
ENGINE_LOG_DEBUG << "Merge index file: " << location << " to: " << location_;
auto to_merge = cache::CpuCacheMgr::GetInstance()->GetIndex(location);
if (!to_merge) {
try {
double physical_size = server::CommonUtil::GetFileSize(location);
server::CollectExecutionEngineMetrics metrics(physical_size);
to_merge = read_index(location);
} catch (std::exception& e) {
ENGINE_LOG_ERROR << e.what();
return Status(DB_ERROR, e.what());
}
}
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to merge";
return Status(DB_ERROR, "index is null");
}
if (auto file_index = std::dynamic_pointer_cast<BFIndex>(to_merge)) {
auto status = index_->Add(file_index->Count(), file_index->GetRawVectors(), file_index->GetRawIds());
if (!status.ok()) {
ENGINE_LOG_ERROR << "Failed to merge: " << location << " to: " << location_;
} else {
ENGINE_LOG_DEBUG << "Finish merge index file: " << location;
}
return status;
} else if (auto bin_index = std::dynamic_pointer_cast<BinBFIndex>(to_merge)) {
auto status = index_->Add(bin_index->Count(), bin_index->GetRawVectors(), bin_index->GetRawIds());
if (!status.ok()) {
ENGINE_LOG_ERROR << "Failed to merge: " << location << " to: " << location_;
} else {
ENGINE_LOG_DEBUG << "Finish merge index file: " << location;
}
return status;
} else {
return Status(DB_ERROR, "file index type is not idmap");
}
}
ExecutionEnginePtr
ExecutionEngineImpl::BuildIndex(const std::string& location, EngineType engine_type) {
ENGINE_LOG_DEBUG << "Build index file: " << location << " from: " << location_;
auto from_index = std::dynamic_pointer_cast<BFIndex>(index_);
auto bin_from_index = std::dynamic_pointer_cast<BinBFIndex>(index_);
if (from_index == nullptr && bin_from_index == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: from_index is null, failed to build index";
return nullptr;
}
auto to_index = CreatetVecIndex(engine_type);
if (!to_index) {
throw Exception(DB_ERROR, "Unsupported index type");
}
TempMetaConf temp_conf;
temp_conf.gpu_id = gpu_num_;
temp_conf.dim = Dimension();
temp_conf.nlist = nlist_;
temp_conf.size = Count();
auto status = MappingMetricType(metric_type_, temp_conf.metric_type);
if (!status.ok()) {
throw Exception(DB_ERROR, status.message());
}
auto adapter = AdapterMgr::GetInstance().GetAdapter(to_index->GetType());
auto conf = adapter->Match(temp_conf);
if (from_index) {
status = to_index->BuildAll(Count(), from_index->GetRawVectors(), from_index->GetRawIds(), conf);
} else if (bin_from_index) {
status = to_index->BuildAll(Count(), bin_from_index->GetRawVectors(), bin_from_index->GetRawIds(), conf);
}
if (!status.ok()) {
throw Exception(DB_ERROR, status.message());
}
ENGINE_LOG_DEBUG << "Finish build index file: " << location << " size: " << to_index->Size();
return std::make_shared<ExecutionEngineImpl>(to_index, location, engine_type, metric_type_, nlist_);
}
Status
ExecutionEngineImpl::Search(int64_t n, const float* data, int64_t k, int64_t nprobe, float* distances, int64_t* labels,
bool hybrid) {
#if 0
if (index_type_ == EngineType::FAISS_IVFSQ8H) {
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);
}
}
}
#endif
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to search";
return Status(DB_ERROR, "index is null");
}
ENGINE_LOG_DEBUG << "Search Params: [k] " << k << " [nprobe] " << nprobe;
// TODO(linxj): remove here. Get conf from function
TempMetaConf temp_conf;
temp_conf.k = k;
temp_conf.nprobe = nprobe;
auto adapter = AdapterMgr::GetInstance().GetAdapter(index_->GetType());
auto conf = adapter->MatchSearch(temp_conf, index_->GetType());
if (hybrid) {
HybridLoad();
}
auto status = index_->Search(n, data, distances, labels, conf);
if (hybrid) {
HybridUnset();
}
if (!status.ok()) {
ENGINE_LOG_ERROR << "Search error:" << status.message();
}
return status;
}
Status
ExecutionEngineImpl::Search(int64_t n, const uint8_t* data, int64_t k, int64_t nprobe, float* distances,
int64_t* labels, bool hybrid) {
if (index_ == nullptr) {
ENGINE_LOG_ERROR << "ExecutionEngineImpl: index is null, failed to search";
return Status(DB_ERROR, "index is null");
}
ENGINE_LOG_DEBUG << "Search Params: [k] " << k << " [nprobe] " << nprobe;
// TODO(linxj): remove here. Get conf from function
TempMetaConf temp_conf;
temp_conf.k = k;
temp_conf.nprobe = nprobe;
auto adapter = AdapterMgr::GetInstance().GetAdapter(index_->GetType());
auto conf = adapter->MatchSearch(temp_conf, index_->GetType());
if (hybrid) {
HybridLoad();
}
auto status = index_->Search(n, data, distances, labels, conf);
if (hybrid) {
HybridUnset();
}
if (!status.ok()) {
ENGINE_LOG_ERROR << "Search error:" << status.message();
}
return status;
}
Status
ExecutionEngineImpl::Cache() {
cache::DataObjPtr obj = std::static_pointer_cast<cache::DataObj>(index_);
milvus::cache::CpuCacheMgr::GetInstance()->InsertItem(location_, obj);
return Status::OK();
}
Status
ExecutionEngineImpl::GpuCache(uint64_t gpu_id) {
#ifdef MILVUS_GPU_VERSION
cache::DataObjPtr obj = std::static_pointer_cast<cache::DataObj>(index_);
milvus::cache::GpuCacheMgr::GetInstance(gpu_id)->InsertItem(location_, obj);
#endif
return Status::OK();
}
// TODO(linxj): remove.
Status
ExecutionEngineImpl::Init() {
#ifdef MILVUS_GPU_VERSION
server::Config& config = server::Config::GetInstance();
std::vector<int64_t> gpu_ids;
Status s = config.GetGpuResourceConfigBuildIndexResources(gpu_ids);
if (!s.ok()) {
gpu_num_ = knowhere::INVALID_VALUE;
return s;
}
for (auto id : gpu_ids) {
if (gpu_num_ == id) {
return Status::OK();
}
}
std::string msg = "Invalid gpu_num";
return Status(SERVER_INVALID_ARGUMENT, msg);
#else
return Status::OK();
#endif
}
} // namespace engine
} // namespace milvus