Various fixes to reproducible benchmarks

cpp/bench/ann/src/common/util.hpp

@@ -91,9 +91,15 @@ struct buf {
 
 struct cuda_timer {
  private:
+#ifndef BUILD_CPU_ONLY
   cudaStream_t stream_{nullptr};
   cudaEvent_t start_{nullptr};
   cudaEvent_t stop_{nullptr};
+#else
+  cudaStream_t stream_{0};
+  cudaEvent_t start_{0};
+  cudaEvent_t stop_{0};
+#endif
   double total_time_{0};
 
  public:

cpp/bench/ann/src/ggnn/ggnn_benchmark.cu

@@ -33,8 +33,7 @@ template <typename T>
 void parse_build_param(const nlohmann::json& conf,
                        typename raft::bench::ann::Ggnn<T>::BuildParam& param)
 {
-  param.dataset_size = conf.at("dataset_size");
-  param.k            = conf.at("k");
+  param.k = conf.at("k");
 
   if (conf.contains("k_build")) { param.k_build = conf.at("k_build"); }
   if (conf.contains("segment_size")) { param.segment_size = conf.at("segment_size"); }

cpp/bench/ann/src/ggnn/ggnn_wrapper.cuh

@@ -38,8 +38,6 @@ class Ggnn : public ANN<T> {
     int num_layers{4};     // L
     float tau{0.5};
     int refine_iterations{2};
-
-    size_t dataset_size;
     int k;  // GGNN requires to know k during building
   };
 
@@ -182,24 +180,17 @@ GgnnImpl<T, measure, D, KBuild, KQuery, S>::GgnnImpl(Metric metric,
   }
 
   if (dim != D) { throw std::runtime_error("mis-matched dim"); }
-
-  int device;
-  RAFT_CUDA_TRY(cudaGetDevice(&device));
-
-  ggnn_ = std::make_unique<GGNNGPUInstance>(
-    device, build_param_.dataset_size, build_param_.num_layers, true, build_param_.tau);
 }
 
 template <typename T, DistanceMeasure measure, int D, int KBuild, int KQuery, int S>
 void GgnnImpl<T, measure, D, KBuild, KQuery, S>::build(const T* dataset,
                                                        size_t nrow,
                                                        cudaStream_t stream)
 {
-  if (nrow != build_param_.dataset_size) {
-    throw std::runtime_error(
-      "build_param_.dataset_size = " + std::to_string(build_param_.dataset_size) +
-      " , but nrow = " + std::to_string(nrow));
-  }
+  int device;
+  RAFT_CUDA_TRY(cudaGetDevice(&device));
+  ggnn_ = std::make_unique<GGNNGPUInstance>(
+    device, nrow, build_param_.num_layers, true, build_param_.tau);
 
   ggnn_->set_base_data(dataset);
   ggnn_->set_stream(stream);
@@ -212,11 +203,6 @@ void GgnnImpl<T, measure, D, KBuild, KQuery, S>::build(const T* dataset,
 template <typename T, DistanceMeasure measure, int D, int KBuild, int KQuery, int S>
 void GgnnImpl<T, measure, D, KBuild, KQuery, S>::set_search_dataset(const T* dataset, size_t nrow)
 {
-  if (nrow != build_param_.dataset_size) {
-    throw std::runtime_error(
-      "build_param_.dataset_size = " + std::to_string(build_param_.dataset_size) +
-      " , but nrow = " + std::to_string(nrow));
-  }
   ggnn_->set_base_data(dataset);
 }
 

cpp/bench/ann/src/hnswlib/hnswlib_wrapper.h

@@ -31,6 +31,8 @@
 #include <utility>
 #include <vector>
 
+#include <omp.h>
+
 #include "../common/ann_types.hpp"
 #include <hnswlib.h>
 
@@ -164,13 +166,13 @@ class HnswLib : public ANN<T> {
   struct BuildParam {
     int M;
     int ef_construction;
-    int num_threads{1};
+    int num_threads = omp_get_num_procs();
   };
 
   using typename ANN<T>::AnnSearchParam;
   struct SearchParam : public AnnSearchParam {
     int ef;
-    int num_threads{1};
+    int num_threads = omp_get_num_procs();
   };
 
   HnswLib(Metric metric, int dim, const BuildParam& param);

docs/source/ann_benchmarks_param_tuning.md

@@ -81,6 +81,28 @@ IVF-pq is an inverted-file index, which partitions the vectors into a series of
 
 ### `hnswlib`
 
+
+| Parameter        | Type            | Required | Data Type                            | Default | Description                                                                                                                                                                                                                                                                                       |
+|------------------|-----------------|----------|--------------------------------------|---------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| `efConstruction` | `build_param`   | Y        | Positive Integer >0                  |         | Controls index time and accuracy. Bigger values increase the index quality. At some point, increasing this will no longer improve the quality.                                                                                                                                                    |
+| `M`              | `build_param`   | Y        | Positive Integer often between 2-100 |         | Number of bi-directional links create for every new element during construction. Higher values work for higher intrinsic dimensionality and/or high recall, low values can work for datasets with low intrinsic dimensionality and/or low recalls. Also affects the algorithm's memory consumption. |
+| `numThreads`     | `build_param`   | N        | Positive Integer >0                  | 1       | Number of threads to use to build the index.                                                                                                                                                                                                                                                      |
+| `ef`             | `search_param`  | Y        | Positive Integer >0                  |         | Size of the dynamic list for the nearest neighbors used for search. Higher value leads to more accurate but slower search. Cannot be lower than `k`.                                                                                                                                              |
+| `numThreads`     | `search_params` | N        | Positive Integer >0                  | 1       | Number of threads to use for queries.                                                                                                                                                                                                                                                             |
+
+Please refer to [HNSW algorithm parameters guide] from `hnswlib` to learn more about these arguments.
+
 ## GGNN Index
 
 ### `ggnn`
+
+
+| Parameter      | Type            | Required | Data Type                            | Default     | Description                                                                                                                                                                                                                                                                                       |
+|----------------|-----------------|----------|--------------------------------------|-------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| `dataset_size` | `build_param`   | Y        | Positive Integer >0                  |             | Controls index time and accuracy. Bigger values increase the index quality. At some point, increasing this will no longer improve the quality.                                                                                                                                                    |
+| `M`            | `build_param`   | Y        | Positive Integer often between 2-100 |             | Number of bi-directional links create for every new element during construction. Higher values work for higher intrinsic dimensionality and/or high recall, low values can work for datasets with low intrinsic dimensionality and/or low recalls. Also affects the algorithm's memory consumption. |
+| `numThreads`   | `build_param`   | N        | Positive Integer >0                  | # cpu cores | Number of threads to use to build the index.                                                                                                                                                                                                                                                      |
+| `ef`           | `search_param`  | Y        | Positive Integer >0                  |             | Size of the dynamic list for the nearest neighbors used for search. Higher value leads to more accurate but slower search. Cannot be lower than `k`.                                                                                                                                              |
+| `numThreads`   | `search_params` | N        | Positive Integer >0                  | # cpu cores | Number of threads to use for queries.                                                                                                                                                                                                                                                             |
+
+