[Outdated] Scaling workspace resources

cpp/include/raft/neighbors/detail/cagra/cagra_build.cuh

@@ -93,11 +93,26 @@ void build_knn_graph(raft::resources const& res,
     search_params->lut_dtype = CUDA_R_8U;
     search_params->internal_distance_dtype = CUDA_R_32F;
   }
-  const auto top_k          = node_degree + 1;
-  uint32_t gpu_top_k        = node_degree * refine_rate.value_or(2.0f);
-  gpu_top_k                 = std::min<IdxT>(std::max(gpu_top_k, top_k), dataset.extent(0));
-  const auto num_queries    = dataset.extent(0);
-  const auto max_batch_size = 1024;
+  const auto top_k       = node_degree + 1;
+  uint32_t gpu_top_k     = node_degree * refine_rate.value_or(2.0f);
+  gpu_top_k              = std::min<IdxT>(std::max(gpu_top_k, top_k), dataset.extent(0));
+  const auto num_queries = dataset.extent(0);
+  rmm::device_async_resource_ref workspace_mr = raft::resource::get_workspace_resource(res);
+
+  constexpr size_t kDefaultBatchSize = 1024;
+  constexpr size_t kMaxBatchSize     = 4096;  // No more perf beyond this
+  constexpr size_t kMinBatchSize     = 128;   // Too slow if smaller
+  // Heuristic: how much of the workspace we can spare for the queries.
+  // The rest is going to be used by ivf_pq::search
+  const auto workspace_queries_bytes = raft::resource::get_workspace_free_bytes(res) / 5;
+  auto max_batch_size =
+    std::min<size_t>(workspace_queries_bytes / sizeof(DataT) / dataset.extent(1), kMaxBatchSize);
+  // Heuristic: if the workspace is too small for a decent batch size, switch to use the large
+  // resource with a default batch size.
+  if (max_batch_size < kMinBatchSize) {
+    max_batch_size = kDefaultBatchSize;
+    workspace_mr   = raft::resource::get_large_workspace_resource(res);
+  }
   RAFT_LOG_DEBUG(
     "IVF-PQ search node_degree: %d, top_k: %d,  gpu_top_k: %d,  max_batch_size:: %d, n_probes: %u",
     node_degree,
@@ -106,12 +121,17 @@ void build_knn_graph(raft::resources const& res,
     max_batch_size,
     search_params->n_probes);
 
-  auto distances = raft::make_device_matrix<float, int64_t>(res, max_batch_size, gpu_top_k);
-  auto neighbors = raft::make_device_matrix<int64_t, int64_t>(res, max_batch_size, gpu_top_k);
-  auto refined_distances = raft::make_device_matrix<float, int64_t>(res, max_batch_size, top_k);
-  auto refined_neighbors = raft::make_device_matrix<int64_t, int64_t>(res, max_batch_size, top_k);
-  auto neighbors_host    = raft::make_host_matrix<int64_t, int64_t>(max_batch_size, gpu_top_k);
-  auto queries_host = raft::make_host_matrix<DataT, int64_t>(max_batch_size, dataset.extent(1));
+  rmm::device_async_resource_ref large_mr = raft::resource::get_large_workspace_resource(res);
+  auto distances                          = raft::make_device_mdarray<float>(
+    res, large_mr, raft::make_extents<int64_t>(max_batch_size, gpu_top_k));
+  auto neighbors = raft::make_device_mdarray<int64_t>(
+    res, large_mr, raft::make_extents<int64_t>(max_batch_size, gpu_top_k));
+  auto refined_distances = raft::make_device_mdarray<float>(
+    res, large_mr, raft::make_extents<int64_t>(max_batch_size, top_k));
+  auto refined_neighbors = raft::make_device_mdarray<int64_t>(
+    res, large_mr, raft::make_extents<int64_t>(max_batch_size, top_k));
+  auto neighbors_host = raft::make_host_matrix<int64_t, int64_t>(max_batch_size, gpu_top_k);
+  auto queries_host   = raft::make_host_matrix<DataT, int64_t>(max_batch_size, dataset.extent(1));
   auto refined_neighbors_host = raft::make_host_matrix<int64_t, int64_t>(max_batch_size, top_k);
   auto refined_distances_host = raft::make_host_matrix<float, int64_t>(max_batch_size, top_k);
 
@@ -120,15 +140,13 @@ void build_knn_graph(raft::resources const& res,
   bool first                    = true;
   const auto start_clock        = std::chrono::system_clock::now();
 
-  rmm::device_async_resource_ref device_memory = raft::resource::get_workspace_resource(res);
-
   raft::spatial::knn::detail::utils::batch_load_iterator<DataT> vec_batches(
     dataset.data_handle(),
     dataset.extent(0),
     dataset.extent(1),
     max_batch_size,
     resource::get_cuda_stream(res),
-    device_memory);
+    workspace_mr);
 
   size_t next_report_offset = 0;
   size_t d_report_offset    = dataset.extent(0) / 100;  // Report progress in 1% steps.

cpp/include/raft/neighbors/detail/cagra/graph_core.cuh

@@ -246,15 +246,19 @@ void sort_knn_graph(raft::resources const& res,
   const uint32_t input_graph_degree = knn_graph.extent(1);
   IdxT* const input_graph_ptr       = knn_graph.data_handle();
 
-  auto d_input_graph = raft::make_device_matrix<IdxT, int64_t>(res, graph_size, input_graph_degree);
+  auto large_tmp_mr = resource::get_large_workspace_resource(res);
+
+  auto d_input_graph = raft::make_device_mdarray<IdxT>(
+    res, large_tmp_mr, raft::make_extents<int64_t>(graph_size, input_graph_degree));
 
   //
   // Sorting kNN graph
   //
   const double time_sort_start = cur_time();
   RAFT_LOG_DEBUG("# Sorting kNN Graph on GPUs ");
 
-  auto d_dataset = raft::make_device_matrix<DataT, int64_t>(res, dataset_size, dataset_dim);
+  auto d_dataset = raft::make_device_mdarray<DataT>(
+    res, large_tmp_mr, raft::make_extents<int64_t>(dataset_size, dataset_dim));
   raft::copy(d_dataset.data_handle(),
              dataset_ptr,
              dataset_size * dataset_dim,
@@ -325,6 +329,7 @@ void optimize(raft::resources const& res,
 {
   RAFT_LOG_DEBUG(
     "# Pruning kNN graph (size=%lu, degree=%lu)\n", knn_graph.extent(0), knn_graph.extent(1));
+  auto large_tmp_mr = resource::get_large_workspace_resource(res);
 
   RAFT_EXPECTS(knn_graph.extent(0) == new_graph.extent(0),
                "Each input array is expected to have the same number of rows");
@@ -340,15 +345,16 @@ void optimize(raft::resources const& res,
     //
     // Prune kNN graph
     //
-    auto d_detour_count =
-      raft::make_device_matrix<uint8_t, int64_t>(res, graph_size, input_graph_degree);
+    auto d_detour_count = raft::make_device_mdarray<uint8_t>(
+      res, large_tmp_mr, raft::make_extents<int64_t>(graph_size, input_graph_degree));
 
     RAFT_CUDA_TRY(cudaMemsetAsync(d_detour_count.data_handle(),
                                   0xff,
                                   graph_size * input_graph_degree * sizeof(uint8_t),
                                   resource::get_cuda_stream(res)));
 
-    auto d_num_no_detour_edges = raft::make_device_vector<uint32_t, int64_t>(res, graph_size);
+    auto d_num_no_detour_edges = raft::make_device_mdarray<uint32_t>(
+      res, large_tmp_mr, raft::make_extents<int64_t>(graph_size));
     RAFT_CUDA_TRY(cudaMemsetAsync(d_num_no_detour_edges.data_handle(),
                                   0x00,
                                   graph_size * sizeof(uint32_t),
@@ -468,14 +474,16 @@ void optimize(raft::resources const& res,
                                   graph_size * output_graph_degree * sizeof(IdxT),
                                   resource::get_cuda_stream(res)));
 
-    auto d_rev_graph_count = raft::make_device_vector<uint32_t, int64_t>(res, graph_size);
+    auto d_rev_graph_count = raft::make_device_mdarray<uint32_t>(
+      res, large_tmp_mr, raft::make_extents<int64_t>(graph_size));
     RAFT_CUDA_TRY(cudaMemsetAsync(d_rev_graph_count.data_handle(),
                                   0x00,
                                   graph_size * sizeof(uint32_t),
                                   resource::get_cuda_stream(res)));
 
-    auto dest_nodes   = raft::make_host_vector<IdxT, int64_t>(graph_size);
-    auto d_dest_nodes = raft::make_device_vector<IdxT, int64_t>(res, graph_size);
+    auto dest_nodes = raft::make_host_vector<IdxT, int64_t>(graph_size);
+    auto d_dest_nodes =
+      raft::make_device_mdarray<IdxT>(res, large_tmp_mr, raft::make_extents<int64_t>(graph_size));
 
     for (uint64_t k = 0; k < output_graph_degree; k++) {
 #pragma omp parallel for

cpp/include/raft/neighbors/detail/cagra/utils.hpp

@@ -184,8 +184,11 @@ class device_matrix_view_from_host {
     device_ptr = reinterpret_cast<T*>(attr.devicePointer);
     if (device_ptr == NULL) {
       // allocate memory and copy over
-      device_mem_.emplace(
-        raft::make_device_matrix<T, IdxT>(res, host_view.extent(0), host_view.extent(1)));
+      // NB: We use the temporary "large" workspace resource here; this structure is supposed to
+      // live on stack and not returned to a user.
+      // The user may opt to set this resource to managed memory to allow large allocations.
+      device_mem_.emplace(make_device_mdarray<T, IdxT>(
+        res, resource::get_large_workspace_resource(res), host_view.extents()));
       raft::copy(device_mem_->data_handle(),
                  host_view.data_handle(),
                  host_view.extent(0) * host_view.extent(1),

cpp/include/raft/neighbors/detail/ivf_flat_build.cuh

@@ -22,6 +22,7 @@
 #include <raft/core/nvtx.hpp>
 #include <raft/core/operators.hpp>
 #include <raft/core/resource/cuda_stream.hpp>
+#include <raft/core/resource/device_memory_resource.hpp>
 #include <raft/core/resources.hpp>
 #include <raft/linalg/add.cuh>
 #include <raft/linalg/map.cuh>
@@ -180,7 +181,8 @@ void extend(raft::resources const& handle,
   RAFT_EXPECTS(new_indices != nullptr || index->size() == 0,
                "You must pass data indices when the index is non-empty.");
 
-  auto new_labels = raft::make_device_vector<LabelT, IdxT>(handle, n_rows);
+  auto new_labels = raft::make_device_mdarray<LabelT>(
+    handle, resource::get_large_workspace_resource(handle), raft::make_extents<IdxT>(n_rows));
   raft::cluster::kmeans_balanced_params kmeans_params;
   kmeans_params.metric = index->metric();
   auto orig_centroids_view =
@@ -211,7 +213,8 @@ void extend(raft::resources const& handle,
   }
 
   auto* list_sizes_ptr    = index->list_sizes().data_handle();
-  auto old_list_sizes_dev = raft::make_device_vector<uint32_t, IdxT>(handle, n_lists);
+  auto old_list_sizes_dev = raft::make_device_mdarray<uint32_t>(
+    handle, resource::get_workspace_resource(handle), raft::make_extents<IdxT>(n_lists));
   copy(old_list_sizes_dev.data_handle(), list_sizes_ptr, n_lists, stream);
 
   // Calculate the centers and sizes on the new data, starting from the original values
@@ -367,7 +370,8 @@ inline auto build(raft::resources const& handle,
     auto trainset_ratio = std::max<size_t>(
       1, n_rows / std::max<size_t>(params.kmeans_trainset_fraction * n_rows, index.n_lists()));
     auto n_rows_train = n_rows / trainset_ratio;
-    rmm::device_uvector<T> trainset(n_rows_train * index.dim(), stream);
+    rmm::device_uvector<T> trainset(
+      n_rows_train * index.dim(), stream, raft::resource::get_large_workspace_resource(handle));
     // TODO: a proper sampling
     RAFT_CUDA_TRY(cudaMemcpy2DAsync(trainset.data(),
                                     sizeof(T) * index.dim(),
@@ -427,7 +431,8 @@ inline void fill_refinement_index(raft::resources const& handle,
   common::nvtx::range<common::nvtx::domain::raft> fun_scope(
     "ivf_flat::fill_refinement_index(%zu, %u)", size_t(n_queries));
 
-  rmm::device_uvector<LabelT> new_labels(n_queries * n_candidates, stream);
+  rmm::device_uvector<LabelT> new_labels(
+    n_queries * n_candidates, stream, raft::resource::get_workspace_resource(handle));
   auto new_labels_view =
     raft::make_device_vector_view<LabelT, IdxT>(new_labels.data(), n_queries * n_candidates);
   linalg::map_offset(

cpp/include/raft/neighbors/detail/ivf_flat_search-ext.cuh

@@ -39,8 +39,8 @@ void search(raft::resources const& handle,
             uint32_t k,
             IdxT* neighbors,
             float* distances,
-            rmm::device_async_resource_ref mr,
-            IvfSampleFilterT sample_filter = IvfSampleFilterT()) RAFT_EXPLICIT;
+            std::optional<rmm::device_async_resource_ref> mr = std::nullopt,
+            IvfSampleFilterT sample_filter                   = IvfSampleFilterT()) RAFT_EXPLICIT;
 
 }  // namespace raft::neighbors::ivf_flat::detail
 
@@ -56,7 +56,7 @@ void search(raft::resources const& handle,
     uint32_t k,                                                                      \
     IdxT* neighbors,                                                                 \
     float* distances,                                                                \
-    rmm::device_async_resource_ref mr,                                               \
+    std::optional<rmm::device_async_resource_ref> mr,                                \
     IvfSampleFilterT sample_filter)
 
 instantiate_raft_neighbors_ivf_flat_detail_search(

cpp/include/raft/neighbors/detail/ivf_flat_search-inl.cuh

@@ -18,6 +18,7 @@
 
 #include <raft/core/logger.hpp>  // RAFT_LOG_TRACE
 #include <raft/core/resource/cuda_stream.hpp>
+#include <raft/core/resource/device_memory_resource.hpp>        // workspace resource
 #include <raft/core/resources.hpp>                              // raft::resources
 #include <raft/distance/distance_types.hpp>                     // is_min_close, DistanceType
 #include <raft/linalg/gemm.cuh>                                 // raft::linalg::gemm
@@ -276,8 +277,8 @@ inline void search(raft::resources const& handle,
                    uint32_t k,
                    IdxT* neighbors,
                    float* distances,
-                   rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource(),
-                   IvfSampleFilterT sample_filter    = IvfSampleFilterT())
+                   std::optional<rmm::device_async_resource_ref> mr = std::nullopt,
+                   IvfSampleFilterT sample_filter                   = IvfSampleFilterT())
 {
   common::nvtx::range<common::nvtx::domain::raft> fun_scope(
     "ivf_flat::search(k = %u, n_queries = %u, dim = %zu)", k, n_queries, index.dim());
@@ -297,15 +298,18 @@ inline void search(raft::resources const& handle,
   }
 
   // a batch size heuristic: try to keep the workspace within the specified size
-  constexpr uint64_t kExpectedWsSize = 1024 * 1024 * 1024;
-  uint64_t max_ws_size = std::min(resource::get_workspace_free_bytes(handle), kExpectedWsSize);
+  uint64_t expected_ws_size = 1024 * 1024 * 1024ull;
+  if (!mr.has_value()) {
+    mr.emplace(resource::get_workspace_resource(handle));
+    expected_ws_size = resource::get_workspace_free_bytes(handle);
+  }
 
   uint64_t ws_size_per_query = 4ull * (2 * n_probes + index.n_lists() + index.dim() + 1) +
                                (manage_local_topk ? ((sizeof(IdxT) + 4) * n_probes * k)
                                                   : (4ull * (max_samples + n_probes + 1)));
 
   const uint32_t max_queries =
-    std::min<uint32_t>(n_queries, raft::div_rounding_up_safe(max_ws_size, ws_size_per_query));
+    std::min<uint32_t>(n_queries, raft::div_rounding_up_safe(expected_ws_size, ws_size_per_query));
 
   for (uint32_t offset_q = 0; offset_q < n_queries; offset_q += max_queries) {
     uint32_t queries_batch = min(max_queries, n_queries - offset_q);
@@ -321,7 +325,7 @@ inline void search(raft::resources const& handle,
                                                   raft::distance::is_min_close(index.metric()),
                                                   neighbors + offset_q * k,
                                                   distances + offset_q * k,
-                                                  mr,
+                                                  mr.value(),
                                                   sample_filter);
   }
 }