Merge remote-tracking branch 'main/0.5.1' into 0.5.1

Former-commit-id: b032e22a12f4b08b6944e8645e7ecd36da02dd4d

CHANGELOG.md

@@ -14,6 +14,7 @@ Please mark all change in change log and use the ticket from JIRA.
 - \#115 - Using new structure for tasktable
 - \#139 - New config option use_gpu_threshold
 - \#146 - Add only GPU and only CPU version for IVF_SQ8 and IVF_FLAT
+- \#164 - Add CPU version for building index
 
 ## Improvement
 - \#64 - Improvement dump function in scheduler
@@ -26,6 +27,7 @@ Please mark all change in change log and use the ticket from JIRA.
 - \#130 - Set task state MOVED after resource copy it completed
 - \#149 - Improve large query optimizer pass
 - \#156 - Not return error when search_resources and index_build_device set cpu
+- \#159 - Change the configuration name from 'use_gpu_threshold' to 'gpu_search_threshold'
 
 ## Task
 

README_CN.md

+![Milvuslogo](https://raw.githubusercontent.com/milvus-io/docs/master/assets/milvus_logo.png)
+
+![LICENSE](https://img.shields.io/badge/license-Apache--2.0-brightgreen)
+![Language](https://img.shields.io/badge/language-C%2B%2B-blue)
+[![codebeat badge](https://codebeat.co/badges/e030a4f6-b126-4475-a938-4723d54ec3a7?style=plastic)](https://codebeat.co/projects/github-com-jinhai-cn-milvus-master)
+
+![Release](https://img.shields.io/badge/release-v0.5.0-orange)
+![Release_date](https://img.shields.io/badge/release_date-October-yellowgreen)
+
+- [Slack 频道](https://join.slack.com/t/milvusio/shared_invite/enQtNzY1OTQ0NDI3NjMzLWNmYmM1NmNjOTQ5MGI5NDhhYmRhMGU5M2NhNzhhMDMzY2MzNDdlYjM5ODQ5MmE3ODFlYzU3YjJkNmVlNDQ2ZTk)
+- [Twitter](https://twitter.com/milvusio)
+- [Facebook](https://www.facebook.com/io.milvus.5)
+- [博客](https://www.milvus.io/blog/)
+- [CSDN](https://zilliz.blog.csdn.net/)
+- [中文官网](https://www.milvus.io/zh-CN/)
+
+# 欢迎来到 Milvus
+
+## Milvus 是什么
+
+Milvus 是一款开源的、针对海量特征向量的相似性搜索引擎。基于异构众核计算框架设计，成本更低，性能更好。在有限的计算资源下，十亿向量搜索仅毫秒响应。
+
+Milvus 提供稳定的 Python、Java 以及 C++ 的 API 接口。
+
+通过 [版本发布说明](https://milvus.io/docs/zh-CN/release/v0.5.0/) 获取最新发行版本的 Milvus。
+
+- 异构众核
+
+  Milvus 基于异构众核计算框架设计，成本更低，性能更好。
+
+- 多元化索引
+
+  Milvus 支持多种索引方式，使用量化索引、基于树的索引和图索引等算法。
+
+- 资源智能管理
+
+  Milvus 根据实际数据规模和可利用资源，智能调节优化查询计算和索引构建过程。
+
+- 水平扩容
+
+  Milvus 支持在线 / 离线扩容，仅需执行简单命令，便可弹性伸缩计算节点和存储节点。
+
+- 高可用性
+
+  Milvus 集成了 Kubernetes 框架，能有效避免单点障碍情况的发生。
+
+- 简单易用
+
+  Milvus 安装简单，使用方便，并可使您专注于特征向量。
+
+- 可视化监控
+
+  您可以使用基于 Prometheus 的图形化监控，以便实时跟踪系统性能。
+
+## 整体架构
+
+![Milvus_arch](https://github.com/milvus-io/docs/blob/master/assets/milvus_arch.png)
+
+## 开始使用 Milvus
+
+### 硬件要求
+
+| 硬件设备 | 推荐配置                              |
+| -------- | ------------------------------------- |
+| CPU      | Intel CPU Haswell 及以上              |
+| GPU      | NVIDIA Pascal 系列及以上              |
+| 内存     | 8 GB 或以上（取决于具体向量数据规模） |
+| 硬盘     | SATA 3.0 SSD 及以上                   |
+
+### 使用 Docker
+
+您可以方便地使用 Docker 安装 Milvus。具体请查看 [Milvus 安装指南](https://milvus.io/docs/zh-CN/userguide/install_milvus/)。
+
+### 从源代码编译
+
+#### 软件要求
+
+- Ubuntu 18.04 及以上
+- CMake 3.14 及以上
+- CUDA 10.0 及以上
+- NVIDIA driver 418 及以上
+
+#### 编译
+
+##### 第一步 安装依赖项
+
+```shell
+$ cd [Milvus sourcecode path]/core
+$ ./ubuntu_build_deps.sh
+```
+
+##### 第二步 编译
+
+```shell
+$ cd [Milvus sourcecode path]/core
+$ ./build.sh -t Debug
+or 
+$ ./build.sh -t Release
+```
+
+当您成功编译后，所有 Milvus 必需组件将安装在`[Milvus root path]/core/milvus`路径下。
+
+##### 启动 Milvus 服务
+
+```shell
+$ cd [Milvus root path]/core/milvus
+```
+
+在 `LD_LIBRARY_PATH` 中添加 `lib/` 目录：
+
+```shell
+$ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/milvus/lib
+```
+
+启动 Milvus 服务：
+
+```shell
+$ cd scripts
+$ ./start_server.sh
+```
+
+若要停止 Milvus 服务，请使用如下命令：
+
+```shell
+$ ./stop_server.sh
+```
+
+若需要修改 Milvus 配置文件 `conf/server_config.yaml` 和`conf/log_config.conf`，请查看 [Milvus 配置](https://milvus.io/docs/zh-CN/reference/milvus_config/)。
+
+### 开始您的第一个 Milvus 程序
+
+#### 运行 Python 示例代码
+
+请确保系统的 Python 版本为 [Python 3.5](https://www.python.org/downloads/) 或以上。
+
+安装 Milvus Python SDK。
+
+```shell
+# Install Milvus Python SDK
+$ pip install pymilvus==0.2.3
+```
+
+创建 `example.py` 文件，并向文件中加入 [Python 示例代码](https://github.com/milvus-io/pymilvus/blob/master/examples/advanced_example.py)。
+
+运行示例代码
+
+```shell
+# Run Milvus Python example
+$ python3 example.py
+```
+
+#### 运行 C++ 示例代码
+
+```shell
+ # Run Milvus C++ example
+ $ cd [Milvus root path]/core/milvus/bin
+ $ ./sdk_simple
+```
+
+#### 运行 Java 示例代码
+
+请确保系统的 Java 版本为 Java 8 或以上。
+
+请从[此处](https://github.com/milvus-io/milvus-sdk-java/tree/master/examples)获取 Java 示例代码。
+
+## 贡献者指南
+
+我们由衷欢迎您推送贡献。关于贡献流程的详细信息，请参阅 [贡献者指南](https://github.com/milvus-io/milvus/blob/master/CONTRIBUTING.md)。本项目遵循 Milvus [行为准则](https://github.com/milvus-io/milvus/blob/master/CODE_OF_CONDUCT.md)。如果您希望参与本项目，请遵守该准则的内容。
+
+我们使用 [GitHub issues](https://github.com/milvus-io/milvus/issues/new/choose) 追踪问题和补丁。若您希望提出问题或进行讨论，请加入我们的社区。
+
+## 加入 Milvus 社区
+
+欢迎加入我们的 [Slack 频道](https://join.slack.com/t/milvusio/shared_invite/enQtNzY1OTQ0NDI3NjMzLWNmYmM1NmNjOTQ5MGI5NDhhYmRhMGU5M2NhNzhhMDMzY2MzNDdlYjM5ODQ5MmE3ODFlYzU3YjJkNmVlNDQ2ZTk) 以便与其他用户和贡献者进行交流。
+
+## Milvus 路线图
+
+请阅读我们的[路线图](https://milvus.io/docs/zh-CN/roadmap/)以获得更多即将开发的新功能。
+
+## 相关链接
+
+[Milvus 官方网站](https://www.milvus.io/)
+
+[Milvus 文档](https://www.milvus.io/docs/en/userguide/install_milvus/)
+
+[Milvus 在线训练营](https://github.com/milvus-io/bootcamp)
+
+[Milvus 博客](https://www.milvus.io/blog/)
+
+[Milvus CSDN](https://zilliz.blog.csdn.net/)
+
+[Milvus 路线图](https://milvus.io/docs/en/roadmap/)
+
+## 许可协议
+
+[Apache 许可协议2.0版](https://github.com/milvus-io/milvus/blob/master/LICENSE)
+

core/conf/server_config.template

@@ -36,7 +36,7 @@ cache_config:
 engine_config:
   use_blas_threshold: 20            # if nq <  use_blas_threshold, use SSE, faster with fluctuated response times
                                     # if nq >= use_blas_threshold, use OpenBlas, slower with stable response times
-  use_gpu_threshold: 1000
+  gpu_search_threshold: 1000        # threshold beyond which the search computation is executed on GPUs only
 
 resource_config:
   search_resources:                 # define the GPUs used for search computation, must be in format: gpux

core/src/scheduler/JobMgr.cpp

@@ -104,20 +104,25 @@ JobMgr::build_task(const JobPtr& job) {
 
 void
 JobMgr::calculate_path(const TaskPtr& task) {
-    if (task->type_ != TaskType::SearchTask) {
-        return;
-    }
+    if (task->type_ == TaskType::SearchTask) {
+        if (task->label()->Type() != TaskLabelType::SPECIFIED_RESOURCE) {
+            return;
+        }
 
-    if (task->label()->Type() != TaskLabelType::SPECIFIED_RESOURCE) {
-        return;
+        std::vector<std::string> path;
+        auto spec_label = std::static_pointer_cast<SpecResLabel>(task->label());
+        auto src = res_mgr_->GetDiskResources()[0];
+        auto dest = spec_label->resource();
+        ShortestPath(src.lock(), dest.lock(), res_mgr_, path);
+        task->path() = Path(path, path.size() - 1);
+    } else if (task->type_ == TaskType::BuildIndexTask) {
+        auto spec_label = std::static_pointer_cast<SpecResLabel>(task->label());
+        auto src = res_mgr_->GetDiskResources()[0];
+        auto dest = spec_label->resource();
+        std::vector<std::string> path;
+        ShortestPath(src.lock(), dest.lock(), res_mgr_, path);
+        task->path() = Path(path, path.size() - 1);
     }
-
-    std::vector<std::string> path;
-    auto spec_label = std::static_pointer_cast<SpecResLabel>(task->label());
-    auto src = res_mgr_->GetDiskResources()[0];
-    auto dest = spec_label->resource();
-    ShortestPath(src.lock(), dest.lock(), res_mgr_, path);
-    task->path() = Path(path, path.size() - 1);
 }
 
 }  // namespace scheduler

core/src/scheduler/SchedInst.cpp

@@ -55,8 +55,8 @@ load_simple_config() {
     // get resources
     auto gpu_ids = get_gpu_pool();
 
-    int32_t build_gpu_id;
-    config.GetResourceConfigIndexBuildDevice(build_gpu_id);
+    int32_t index_build_device_id;
+    config.GetResourceConfigIndexBuildDevice(index_build_device_id);
 
     // create and connect
     ResMgrInst::GetInstance()->Add(ResourceFactory::Create("disk", "DISK", 0, true, false));
@@ -70,15 +70,15 @@ load_simple_config() {
     for (auto& gpu_id : gpu_ids) {
         ResMgrInst::GetInstance()->Add(ResourceFactory::Create(std::to_string(gpu_id), "GPU", gpu_id, true, true));
         ResMgrInst::GetInstance()->Connect("cpu", std::to_string(gpu_id), pcie);
-        if (build_gpu_id == gpu_id) {
+        if (index_build_device_id == gpu_id) {
             find_build_gpu_id = true;
         }
     }
 
-    if (not find_build_gpu_id) {
+    if (not find_build_gpu_id && index_build_device_id != server::CPU_DEVICE_ID) {
         ResMgrInst::GetInstance()->Add(
-            ResourceFactory::Create(std::to_string(build_gpu_id), "GPU", build_gpu_id, true, true));
-        ResMgrInst::GetInstance()->Connect("cpu", std::to_string(build_gpu_id), pcie);
+            ResourceFactory::Create(std::to_string(index_build_device_id), "GPU", index_build_device_id, true, true));
+        ResMgrInst::GetInstance()->Connect("cpu", std::to_string(index_build_device_id), pcie);
     }
 }
 

core/src/scheduler/SchedInst.h

@@ -106,7 +106,6 @@ class OptimizerInst {
                         has_cpu = true;
                     }
                 }
-
                 std::vector<PassPtr> pass_list;
                 pass_list.push_back(std::make_shared<LargeSQ8HPass>());
                 pass_list.push_back(std::make_shared<HybridPass>());

core/src/scheduler/TaskCreator.cpp

@@ -70,8 +70,15 @@ TaskCreator::Create(const DeleteJobPtr& job) {
 std::vector<TaskPtr>
 TaskCreator::Create(const BuildIndexJobPtr& job) {
     std::vector<TaskPtr> tasks;
-    // TODO(yukun): remove "disk" hardcode here
-    ResourcePtr res_ptr = ResMgrInst::GetInstance()->GetResource("disk");
+    server::Config& config = server::Config::GetInstance();
+    int32_t build_index_id;
+    Status stat = config.GetResourceConfigIndexBuildDevice(build_index_id);
+    ResourcePtr res_ptr;
+    if (build_index_id == server::CPU_DEVICE_ID) {
+        res_ptr = ResMgrInst::GetInstance()->GetResource("cpu");
+    } else {
+        res_ptr = ResMgrInst::GetInstance()->GetResource(ResourceType::GPU, build_index_id);
+    }
 
     for (auto& to_index_file : job->to_index_files()) {
         auto label = std::make_shared<SpecResLabel>(std::weak_ptr<Resource>(res_ptr));

core/src/scheduler/action/PushTaskToNeighbour.cpp

@@ -138,73 +138,41 @@ Action::SpecifiedResourceLabelTaskScheduler(const ResourceMgrPtr& res_mgr, Resou
                                             std::shared_ptr<LoadCompletedEvent> event) {
     auto task_item = event->task_table_item_;
     auto task = event->task_table_item_->task;
-    if (resource->type() == ResourceType::DISK) {
-        // step 1: calculate shortest path per resource, from disk to compute resource
-        auto compute_resources = res_mgr->GetComputeResources();
-        std::vector<std::vector<std::string>> paths;
-        std::vector<uint64_t> transport_costs;
-        for (auto& res : compute_resources) {
-            std::vector<std::string> path;
-            uint64_t transport_cost = ShortestPath(resource, res, res_mgr, path);
-            transport_costs.push_back(transport_cost);
-            paths.emplace_back(path);
-        }
-        //        if (task->job_.lock()->type() == JobType::SEARCH) {
-        //            auto label = task->label();
-        //            auto spec_label = std::static_pointer_cast<SpecResLabel>(label);
-        //            if (spec_label->resource().lock()->type() == ResourceType::CPU) {
-        //                std::vector<std::string> spec_path;
-        //                spec_path.push_back(spec_label->resource().lock()->name());
-        //                spec_path.push_back(resource->name());
-        //                task->path() = Path(spec_path, spec_path.size() - 1);
-        //            } else {
-        //                // step 2: select min cost, cost(resource) = avg_cost * task_to_do + transport_cost
-        //                uint64_t min_cost = std::numeric_limits<uint64_t>::max();
-        //                uint64_t min_cost_idx = 0;
-        //                for (uint64_t i = 0; i < compute_resources.size(); ++i) {
-        //                    if (compute_resources[i]->TotalTasks() == 0) {
-        //                        min_cost_idx = i;
-        //                        break;
-        //                    }
-        //                    uint64_t cost = compute_resources[i]->TaskAvgCost() *
-        //                    compute_resources[i]->NumOfTaskToExec() +
-        //                                    transport_costs[i];
-        //                    if (min_cost > cost) {
-        //                        min_cost = cost;
-        //                        min_cost_idx = i;
-        //                    }
-        //                }
-        //
-        //                // step 3: set path in task
-        //                Path task_path(paths[min_cost_idx], paths[min_cost_idx].size() - 1);
-        //                task->path() = task_path;
-        //            }
-        //
-        //        } else
-        if (task->job_.lock()->type() == JobType::BUILD) {
-            // step2: Read device id in config
-            // get build index gpu resource
-            server::Config& config = server::Config::GetInstance();
-            int32_t build_index_gpu;
-            Status stat = config.GetResourceConfigIndexBuildDevice(build_index_gpu);
-
-            bool find_gpu_res = false;
-            if (res_mgr->GetResource(ResourceType::GPU, build_index_gpu) != nullptr) {
-                for (uint64_t i = 0; i < compute_resources.size(); ++i) {
-                    if (compute_resources[i]->name() ==
-                        res_mgr->GetResource(ResourceType::GPU, build_index_gpu)->name()) {
-                        find_gpu_res = true;
-                        Path task_path(paths[i], paths[i].size() - 1);
-                        task->path() = task_path;
-                        break;
-                    }
-                }
-            }
-            if (not find_gpu_res) {
-                task->path() = Path(paths[0], paths[0].size() - 1);
-            }
-        }
-    }
+    //    if (resource->type() == ResourceType::DISK) {
+    //        // step 1: calculate shortest path per resource, from disk to compute resource
+    //        auto compute_resources = res_mgr->GetComputeResources();
+    //        std::vector<std::vector<std::string>> paths;
+    //        std::vector<uint64_t> transport_costs;
+    //        for (auto& res : compute_resources) {
+    //            std::vector<std::string> path;
+    //            uint64_t transport_cost = ShortestPath(resource, res, res_mgr, path);
+    //            transport_costs.push_back(transport_cost);
+    //            paths.emplace_back(path);
+    //        }
+    //        if (task->job_.lock()->type() == JobType::BUILD) {
+    //            // step2: Read device id in config
+    //            // get build index gpu resource
+    //            server::Config& config = server::Config::GetInstance();
+    //            int32_t build_index_gpu;
+    //            Status stat = config.GetResourceConfigIndexBuildDevice(build_index_gpu);
+    //
+    //            bool find_gpu_res = false;
+    //            if (res_mgr->GetResource(ResourceType::GPU, build_index_gpu) != nullptr) {
+    //                for (uint64_t i = 0; i < compute_resources.size(); ++i) {
+    //                    if (compute_resources[i]->name() ==
+    //                        res_mgr->GetResource(ResourceType::GPU, build_index_gpu)->name()) {
+    //                        find_gpu_res = true;
+    //                        Path task_path(paths[i], paths[i].size() - 1);
+    //                        task->path() = task_path;
+    //                        break;
+    //                    }
+    //                }
+    //            }
+    //            if (not find_gpu_res) {
+    //                task->path() = Path(paths[0], paths[0].size() - 1);
+    //            }
+    //        }
+    //    }
 
     if (resource->name() == task->path().Last()) {
         resource->WakeupExecutor();

core/src/scheduler/optimizer/LargeSQ8HPass.cpp

@@ -29,7 +29,7 @@ namespace scheduler {
 
 LargeSQ8HPass::LargeSQ8HPass() {
     server::Config& config = server::Config::GetInstance();
-    Status s = config.GetEngineConfigUseGpuThreshold(threshold_);
+    Status s = config.GetEngineConfigGpuSearchThreshold(threshold_);
     if (!s.ok()) {
         threshold_ = std::numeric_limits<int32_t>::max();
     }

core/src/scheduler/optimizer/OnlyGPUPass.cpp

@@ -46,7 +46,7 @@ OnlyGPUPass::Run(const TaskPtr& task) {
     auto label = std::make_shared<SpecResLabel>(std::weak_ptr<Resource>(res_ptr));
     task->label() = label;
 
-    specified_gpu_id_ = specified_gpu_id_++ % gpu_id.size();
+    specified_gpu_id_ = (specified_gpu_id_ + 1) % gpu_id.size();
     return true;
 }
 

core/src/server/Config.cpp

@@ -193,8 +193,8 @@ Config::ValidateConfig() {
         return s;
     }
 
-    int32_t engine_use_gpu_threshold;
-    s = GetEngineConfigUseGpuThreshold(engine_use_gpu_threshold);
+    int32_t engine_gpu_search_threshold;
+    s = GetEngineConfigGpuSearchThreshold(engine_gpu_search_threshold);
     if (!s.ok()) {
         return s;
     }
@@ -330,7 +330,7 @@ Config::ResetDefaultConfig() {
         return s;
     }
 
-    s = SetEngineConfigUseGpuThreshold(CONFIG_ENGINE_USE_GPU_THRESHOLD_DEFAULT);
+    s = SetEngineConfigGpuSearchThreshold(CONFIG_ENGINE_GPU_SEARCH_THRESHOLD_DEFAULT);
     if (!s.ok()) {
         return s;
     }
@@ -463,7 +463,7 @@ Status
 Config::CheckDBConfigArchiveDaysThreshold(const std::string& value) {
     if (!ValidationUtil::ValidateStringIsNumber(value).ok()) {
         std::string msg = "Invalid archive days threshold: " + value +
-                          ". Possible reason: db_config.archive_disk_threshold is invalid.";
+                          ". Possible reason: db_config.archive_days_threshold is invalid.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
     return Status::OK();
@@ -590,15 +590,18 @@ Config::CheckCacheConfigGpuCacheCapacity(const std::string& value) {
         return Status(SERVER_INVALID_ARGUMENT, msg);
     } else {
         uint64_t gpu_cache_capacity = std::stoi(value) * GB;
-        int gpu_index;
-        Status s = GetResourceConfigIndexBuildDevice(gpu_index);
+        int device_id;
+        Status s = GetResourceConfigIndexBuildDevice(device_id);
         if (!s.ok()) {
             return s;
         }
 
+        if (device_id == server::CPU_DEVICE_ID)
+            return Status::OK();
+
         size_t gpu_memory;
-        if (!ValidationUtil::GetGpuMemory(gpu_index, gpu_memory).ok()) {
-            std::string msg = "Fail to get GPU memory for GPU device: " + std::to_string(gpu_index);
+        if (!ValidationUtil::GetGpuMemory(device_id, gpu_memory).ok()) {
+            std::string msg = "Fail to get GPU memory for GPU device: " + std::to_string(device_id);
             return Status(SERVER_UNEXPECTED_ERROR, msg);
         } else if (gpu_cache_capacity >= gpu_memory) {
             std::string msg = "Invalid gpu cache capacity: " + value +
@@ -631,7 +634,7 @@ Config::CheckCacheConfigGpuCacheThreshold(const std::string& value) {
 Status
 Config::CheckCacheConfigCacheInsertData(const std::string& value) {
     if (!ValidationUtil::ValidateStringIsBool(value).ok()) {
-        std::string msg = "Invalid cache insert option: " + value +
+        std::string msg = "Invalid cache insert data option: " + value +
                           ". Possible reason: cache_config.cache_insert_data is not a boolean.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
@@ -641,7 +644,7 @@ Config::CheckCacheConfigCacheInsertData(const std::string& value) {
 Status
 Config::CheckEngineConfigUseBlasThreshold(const std::string& value) {
     if (!ValidationUtil::ValidateStringIsNumber(value).ok()) {
-        std::string msg = "Invalid blas threshold: " + value +
+        std::string msg = "Invalid use blas threshold: " + value +
                           ". Possible reason: engine_config.use_blas_threshold is not a positive integer.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
@@ -651,7 +654,7 @@ Config::CheckEngineConfigUseBlasThreshold(const std::string& value) {
 Status
 Config::CheckEngineConfigOmpThreadNum(const std::string& value) {
     if (!ValidationUtil::ValidateStringIsNumber(value).ok()) {
-        std::string msg = "Invalid omp thread number: " + value +
+        std::string msg = "Invalid omp thread num: " + value +
                           ". Possible reason: engine_config.omp_thread_num is not a positive integer.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
@@ -660,7 +663,7 @@ Config::CheckEngineConfigOmpThreadNum(const std::string& value) {
     uint32_t sys_thread_cnt = 8;
     CommonUtil::GetSystemAvailableThreads(sys_thread_cnt);
     if (omp_thread > static_cast<int32_t>(sys_thread_cnt)) {
-        std::string msg = "Invalid omp thread number: " + value +
+        std::string msg = "Invalid omp thread num: " + value +
                           ". Possible reason: engine_config.omp_thread_num exceeds system cpu cores.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
@@ -668,10 +671,10 @@ Config::CheckEngineConfigOmpThreadNum(const std::string& value) {
 }
 
 Status
-Config::CheckEngineConfigUseGpuThreshold(const std::string& value) {
+Config::CheckEngineConfigGpuSearchThreshold(const std::string& value) {
     if (!ValidationUtil::ValidateStringIsNumber(value).ok()) {
-        std::string msg = "Invalid gpu threshold: " + value +
-                          ". Possible reason: engine_config.use_gpu_threshold is not a positive integer.";
+        std::string msg = "Invalid gpu search threshold: " + value +
+                          ". Possible reason: engine_config.gpu_search_threshold is not a positive integer.";
         return Status(SERVER_INVALID_ARGUMENT, msg);
     }
     return Status::OK();
@@ -979,10 +982,10 @@ Config::GetEngineConfigOmpThreadNum(int32_t& value) {
 }
 
 Status
-Config::GetEngineConfigUseGpuThreshold(int32_t& value) {
+Config::GetEngineConfigGpuSearchThreshold(int32_t& value) {
     std::string str =
-        GetConfigStr(CONFIG_ENGINE, CONFIG_ENGINE_USE_GPU_THRESHOLD, CONFIG_ENGINE_USE_GPU_THRESHOLD_DEFAULT);
-    Status s = CheckEngineConfigUseGpuThreshold(str);
+        GetConfigStr(CONFIG_ENGINE, CONFIG_ENGINE_GPU_SEARCH_THRESHOLD, CONFIG_ENGINE_GPU_SEARCH_THRESHOLD_DEFAULT);
+    Status s = CheckEngineConfigGpuSearchThreshold(str);
     if (!s.ok()) {
         return s;
     }
@@ -1013,7 +1016,12 @@ Config::GetResourceConfigIndexBuildDevice(int32_t& value) {
         return s;
     }
 
-    value = std::stoi(str.substr(3));
+    if (str == "cpu") {
+        value = CPU_DEVICE_ID;
+    } else {
+        value = std::stoi(str.substr(3));
+    }
+
     return Status::OK();
 }
 
@@ -1244,13 +1252,13 @@ Config::SetEngineConfigOmpThreadNum(const std::string& value) {
 }
 
 Status
-Config::SetEngineConfigUseGpuThreshold(const std::string& value) {
-    Status s = CheckEngineConfigUseGpuThreshold(value);
+Config::SetEngineConfigGpuSearchThreshold(const std::string& value) {
+    Status s = CheckEngineConfigGpuSearchThreshold(value);
     if (!s.ok()) {
         return s;
     }
 
-    SetConfigValueInMem(CONFIG_DB, CONFIG_ENGINE_USE_GPU_THRESHOLD, value);
+    SetConfigValueInMem(CONFIG_DB, CONFIG_ENGINE_GPU_SEARCH_THRESHOLD, value);
     return Status::OK();
 }
 

core/src/server/Config.h

@@ -84,8 +84,8 @@ static const char* CONFIG_ENGINE_USE_BLAS_THRESHOLD = "use_blas_threshold";
 static const char* CONFIG_ENGINE_USE_BLAS_THRESHOLD_DEFAULT = "20";
 static const char* CONFIG_ENGINE_OMP_THREAD_NUM = "omp_thread_num";
 static const char* CONFIG_ENGINE_OMP_THREAD_NUM_DEFAULT = "0";
-static const char* CONFIG_ENGINE_USE_GPU_THRESHOLD = "use_gpu_threshold";
-static const char* CONFIG_ENGINE_USE_GPU_THRESHOLD_DEFAULT = "1000";
+static const char* CONFIG_ENGINE_GPU_SEARCH_THRESHOLD = "gpu_search_threshold";
+static const char* CONFIG_ENGINE_GPU_SEARCH_THRESHOLD_DEFAULT = "1000";
 
 /* resource config */
 static const char* CONFIG_RESOURCE = "resource_config";
@@ -95,6 +95,8 @@ static const char* CONFIG_RESOURCE_SEARCH_RESOURCES = "search_resources";
 static const char* CONFIG_RESOURCE_INDEX_BUILD_DEVICE = "index_build_device";
 static const char* CONFIG_RESOURCE_INDEX_BUILD_DEVICE_DEFAULT = "gpu0";
 
+const int32_t CPU_DEVICE_ID = -1;
+
 class Config {
  public:
     static Config&
@@ -169,7 +171,7 @@ class Config {
     Status
     CheckEngineConfigOmpThreadNum(const std::string& value);
     Status
-    CheckEngineConfigUseGpuThreshold(const std::string& value);
+    CheckEngineConfigGpuSearchThreshold(const std::string& value);
 
     /* resource config */
     Status
@@ -235,7 +237,7 @@ class Config {
     Status
     GetEngineConfigOmpThreadNum(int32_t& value);
     Status
-    GetEngineConfigUseGpuThreshold(int32_t& value);
+    GetEngineConfigGpuSearchThreshold(int32_t& value);
 
     /* resource config */
     Status
@@ -296,7 +298,7 @@ class Config {
     Status
     SetEngineConfigOmpThreadNum(const std::string& value);
     Status
-    SetEngineConfigUseGpuThreshold(const std::string& value);
+    SetEngineConfigGpuSearchThreshold(const std::string& value);
 
     /* resource config */
     Status