From ba923cc09175c793ada63aa930d8d7d486a98c69 Mon Sep 17 00:00:00 2001 From: Dante Gama Dessavre Date: Sun, 24 Sep 2023 22:29:08 -0500 Subject: [PATCH 1/2] raft-ann-bench package fixes for plotting and conf files (#1844) Number of improvements and fixes for different million scale datasets that are supported by default by the python benchmarking package. Authors: - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - Divye Gala (https://github.com/divyegala) URL: https://github.com/rapidsai/raft/pull/1844 --- .../src/raft-ann-bench/plot/__main__.py | 41 +- .../run/conf/deep-image-96-inner.json | 1 + .../run/conf/fashion-mnist-784-euclidean.json | 1 + .../run/conf/glove-100-inner.json | 1766 +++++++++++------ .../run/conf/glove-50-inner.json | 1351 +++++++++++++ .../run/conf/mnist-784-euclidean.json | 1 + .../run/conf/nytimes-256-angular.json | 1 + .../run/conf/nytimes-256-inner.json | 1352 +++++++++++++ 8 files changed, 3923 insertions(+), 591 deletions(-) create mode 100644 python/raft-ann-bench/src/raft-ann-bench/run/conf/glove-50-inner.json create mode 100644 python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-inner.json diff --git a/python/raft-ann-bench/src/raft-ann-bench/plot/__main__.py b/python/raft-ann-bench/src/raft-ann-bench/plot/__main__.py index 198d0a2b14..233607c281 100644 --- a/python/raft-ann-bench/src/raft-ann-bench/plot/__main__.py +++ b/python/raft-ann-bench/src/raft-ann-bench/plot/__main__.py @@ -254,18 +254,18 @@ def create_plot_build( xn = "k-nn" yn = "qps" - # recall_85 = [-1] * len(linestyles) qps_85 = [-1] * len(linestyles) bt_85 = [0] * len(linestyles) i_85 = [-1] * len(linestyles) - # recall_90 = [-1] * len(linestyles) + qps_90 = [-1] * len(linestyles) bt_90 = [0] * len(linestyles) i_90 = [-1] * len(linestyles) - # recall_95 = [-1] * len(linestyles) + qps_95 = [-1] * len(linestyles) bt_95 = [0] * len(linestyles) i_95 = [-1] * len(linestyles) + data = OrderedDict() colors = OrderedDict() @@ -303,7 +303,7 @@ def mean_y(algo): plt.figure(figsize=(12, 9)) ax = df.plot.bar(rot=0, color=colors) fig = ax.get_figure() - print(f"writing search output to {fn_out}") + print(f"writing build output to {fn_out}") plt.title("Build Time for Highest QPS") plt.suptitle(f"{dataset} k={k} batch_size={batch_size}") plt.ylabel("Build Time (s)") @@ -313,35 +313,22 @@ def mean_y(algo): def load_lines(results_path, result_files, method, index_key): results = dict() - linebreaker = "name,iterations" - for result_filename in result_files: if result_filename.endswith(".csv"): with open(os.path.join(results_path, result_filename), "r") as f: lines = f.readlines() lines = lines[:-1] if lines[-1] == "\n" else lines - idx = 0 - for pos, line in enumerate(lines): - if linebreaker in line: - idx = pos - break if method == "build": - if "hnswlib" in result_filename: - key_idx = [2] - else: - key_idx = [10] + key_idx = [2] elif method == "search": - if "hnswlib" in result_filename: - key_idx = [10, 6] - else: - key_idx = [12, 10] + key_idx = [2, 3] - for line in lines[idx + 1 :]: + for line in lines[1:]: split_lines = line.split(",") - algo_name = split_lines[0].split(".")[0].strip('"') - index_name = split_lines[0].split("/")[0].strip('"') + algo_name = split_lines[0] + index_name = split_lines[1] if index_key == "algo": dict_key = algo_name @@ -394,9 +381,7 @@ def main(): ) parser.add_argument( "--dataset-path", - help="path to dataset folder, by default will look in " - "RAPIDS_DATASET_ROOT_DIR if defined, otherwise a datasets " - "subdirectory from the calling directory", + help="path to dataset folder", default=default_dataset_path, ) parser.add_argument( @@ -460,10 +445,12 @@ def main(): search = args.search search_output_filepath = os.path.join( - args.output_filepath, f"search-{args.dataset}-{k}-{batch_size}.png" + args.output_filepath, + f"search-{args.dataset}-k{k}-batch_size{batch_size}.png", ) build_output_filepath = os.path.join( - args.output_filepath, f"build-{args.dataset}-{k}-{batch_size}.png" + args.output_filepath, + f"build-{args.dataset}-k{k}-batch_size{batch_size}.png", ) search_results = load_all_results( diff --git a/python/raft-ann-bench/src/raft-ann-bench/run/conf/deep-image-96-inner.json b/python/raft-ann-bench/src/raft-ann-bench/run/conf/deep-image-96-inner.json index f1c033e415..ab82405439 100644 --- a/python/raft-ann-bench/src/raft-ann-bench/run/conf/deep-image-96-inner.json +++ b/python/raft-ann-bench/src/raft-ann-bench/run/conf/deep-image-96-inner.json @@ -3,6 +3,7 @@ "name": "deep-image-96-inner", "base_file": "deep-image-96-inner/base.fbin", "query_file": "deep-image-96-inner/query.fbin", + "groundtruth_neighbors_file": "deep-image-96-inner/groundtruth.neighbors.ibin", "distance": "euclidean" }, "search_basic_param": { diff --git a/python/raft-ann-bench/src/raft-ann-bench/run/conf/fashion-mnist-784-euclidean.json b/python/raft-ann-bench/src/raft-ann-bench/run/conf/fashion-mnist-784-euclidean.json index 65f28fc81a..0efe1fc498 100644 --- a/python/raft-ann-bench/src/raft-ann-bench/run/conf/fashion-mnist-784-euclidean.json +++ b/python/raft-ann-bench/src/raft-ann-bench/run/conf/fashion-mnist-784-euclidean.json @@ -3,6 +3,7 @@ "name": "fashion-mnist-784-euclidean", "base_file": "fashion-mnist-784-euclidean/base.fbin", "query_file": "fashion-mnist-784-euclidean/query.fbin", + "groundtruth_neighbors_file": "fashion-mnist-784-euclidean/groundtruth.neighbors.ibin", "distance": "euclidean" }, "search_basic_param": { diff --git a/python/raft-ann-bench/src/raft-ann-bench/run/conf/glove-100-inner.json b/python/raft-ann-bench/src/raft-ann-bench/run/conf/glove-100-inner.json index 7c95ceb439..54c8bf908c 100644 --- a/python/raft-ann-bench/src/raft-ann-bench/run/conf/glove-100-inner.json +++ b/python/raft-ann-bench/src/raft-ann-bench/run/conf/glove-100-inner.json @@ -3,711 +3,1349 @@ "name": "glove-100-inner", "base_file": "glove-100-inner/base.fbin", "query_file": "glove-100-inner/query.fbin", - "groundtruth_neighbors_file": "glove-100-inner/groundtruth.neighbors.ibin", - "distance": "inner_product" + "distance": "euclidean" }, - "search_basic_param": { - "batch_size": 1, - "k": 10 + "batch_size": 5000, + "k": 10, + "run_count": 3 }, - "index": [ { - "name": "hnswlib.M4", - "algo": "hnswlib", - "build_param": {"M":4, "efConstruction":500, "numThreads":4}, - "file": 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@@ "name": "mnist-784-euclidean", "base_file": "mnist-784-euclidean/base.fbin", "query_file": "mnist-784-euclidean/query.fbin", + "groundtruth_neighbors_file": "mnist-784-euclidean/groundtruth.neighbors.ibin", "distance": "euclidean" }, "search_basic_param": { diff --git a/python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-angular.json b/python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-angular.json index 630b700ba5..e94a9969d9 100644 --- a/python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-angular.json +++ b/python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-angular.json @@ -3,6 +3,7 @@ "name": "nytimes-256-angular", "base_file": "nytimes-256-angular/base.fbin", "query_file": "nytimes-256-angular/query.fbin", + "groundtruth_neighbors_file": "nytimes-256-angular/groundtruth.neighbors.ibin", "distance": "euclidean" }, "search_basic_param": { diff --git a/python/raft-ann-bench/src/raft-ann-bench/run/conf/nytimes-256-inner.json 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"search_result_file": "result/nytimes-256-inner/raft_ivf_pq/dimpq512-cluster1024-float-float" + }, + { + "name": "raft_ivf_flat.nlist1024", + "algo": "raft_ivf_flat", + "build_param": { + "nlist": 1024, + "ratio": 1, + "niter": 25 + }, + "file": "index/nytimes-256-inner/raft_ivf_flat/nlist1024", + "search_params": [ + { + "nprobe": 1 + }, + { + "nprobe": 5 + }, + { + "nprobe": 10 + }, + { + "nprobe": 50 + }, + { + "nprobe": 100 + }, + { + "nprobe": 200 + }, + { + "nprobe": 500 + }, + { + "nprobe": 1000 + } + ], + "search_result_file": "result/nytimes-256-inner/raft_ivf_flat/nlist1024" + }, + { + "name": "raft_ivf_flat.nlist16384", + "algo": "raft_ivf_flat", + "build_param": { + "nlist": 16384, + "ratio": 2, + "niter": 20 + }, + "file": "index/nytimes-256-inner/raft_ivf_flat/nlist16384", + "search_params": [ + { + "nprobe": 1 + }, + { + "nprobe": 5 + }, + { + "nprobe": 10 + }, + { + "nprobe": 50 + }, + { + "nprobe": 100 + }, + { + "nprobe": 200 + }, + { + "nprobe": 500 + }, + { + "nprobe": 1000 + }, + { + "nprobe": 2000 + } + ], + "search_result_file": "result/nytimes-256-inner/raft_ivf_flat/nlist16384" + }, + + { + "name" : "raft_cagra.dim32", + "algo" : "raft_cagra", + "build_param": { + "graph_degree" : 32 + }, + "file" : "index/nytimes-256-inner/raft_cagra/dim32", + "search_params" : [ + {"itopk": 32}, + {"itopk": 64}, + {"itopk": 128} + ], + "search_result_file" : "result/nytimes-256-inner/raft_cagra/dim32" + }, + + { + "name" : "raft_cagra.dim64", + "algo" : "raft_cagra", + "build_param": { + "graph_degree" : 64 + }, + "file" : "index/nytimes-256-inner/raft_cagra/dim64", + "search_params" : [ + {"itopk": 32}, + {"itopk": 64}, + {"itopk": 128} + ], + "search_result_file" : "result/nytimes-256-inner/raft_cagra/dim64" + } + ] +} From dfde3b499a403af433e1e27b9174461ec086adc9 Mon Sep 17 00:00:00 2001 From: Ben Frederickson Date: Mon, 25 Sep 2023 10:02:07 -0700 Subject: [PATCH 2/2] Fixes for OOM during CAGRA benchmarks (#1832) Running the CAGRA benchmarks and there could be OOM errors on GPU memory with large datasets. This is caused by holding multiple copies of the dataset in GPU memory. Fix by: * Free existing memory for the dataset/graph before allocating new memory during update_dataset/update_grph * On deserialize, if the serialized index doesn't contain the dataset - don't allocate GPU memory for it * Don't call update_dataset repeatedly in the benchmarking code with the same dataset Authors: - Ben Frederickson (https://github.com/benfred) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: https://github.com/rapidsai/raft/pull/1832 --- cpp/include/raft/neighbors/cagra_types.hpp | 19 +++++++++++++++---- .../detail/cagra/cagra_serialize.cuh | 19 +++++++++++++------ 2 files changed, 28 insertions(+), 10 deletions(-) diff --git a/cpp/include/raft/neighbors/cagra_types.hpp b/cpp/include/raft/neighbors/cagra_types.hpp index 02e3f5338e..4728178194 100644 --- a/cpp/include/raft/neighbors/cagra_types.hpp +++ b/cpp/include/raft/neighbors/cagra_types.hpp @@ -165,9 +165,10 @@ struct index : ann::index { ~index() = default; /** Construct an empty index. */ - index(raft::resources const& res) + index(raft::resources const& res, + raft::distance::DistanceType metric = raft::distance::DistanceType::L2Expanded) : ann::index(), - metric_(raft::distance::DistanceType::L2Expanded), + metric_(metric), dataset_(make_device_matrix(res, 0, 0)), graph_(make_device_matrix(res, 0, 0)) { @@ -296,7 +297,11 @@ struct index : ann::index { raft::host_matrix_view knn_graph) { RAFT_LOG_DEBUG("Copying CAGRA knn graph from host to device"); - graph_ = make_device_matrix(res, knn_graph.extent(0), knn_graph.extent(1)); + if ((graph_.extent(0) != knn_graph.extent(0)) || (graph_.extent(1) != knn_graph.extent(1))) { + // clear existing memory before allocating to prevent OOM errors on large graphs + if (graph_.size()) { graph_ = make_device_matrix(res, 0, 0); } + graph_ = make_device_matrix(res, knn_graph.extent(0), knn_graph.extent(1)); + } raft::copy(graph_.data_handle(), knn_graph.data_handle(), knn_graph.size(), @@ -311,7 +316,13 @@ struct index : ann::index { mdspan, row_major, data_accessor> dataset) { size_t padded_dim = round_up_safe(dataset.extent(1) * sizeof(T), 16) / sizeof(T); - dataset_ = make_device_matrix(res, dataset.extent(0), padded_dim); + + if ((dataset_.extent(0) != dataset.extent(0)) || + (static_cast(dataset_.extent(1)) != padded_dim)) { + // clear existing memory before allocating to prevent OOM errors on large datasets + if (dataset_.size()) { dataset_ = make_device_matrix(res, 0, 0); } + dataset_ = make_device_matrix(res, dataset.extent(0), padded_dim); + } if (dataset_.extent(1) == dataset.extent(1)) { raft::copy(dataset_.data_handle(), dataset.data_handle(), diff --git a/cpp/include/raft/neighbors/detail/cagra/cagra_serialize.cuh b/cpp/include/raft/neighbors/detail/cagra/cagra_serialize.cuh index 234911e15c..8261f637e1 100644 --- a/cpp/include/raft/neighbors/detail/cagra/cagra_serialize.cuh +++ b/cpp/include/raft/neighbors/detail/cagra/cagra_serialize.cuh @@ -130,15 +130,22 @@ auto deserialize(raft::resources const& res, std::istream& is) -> index auto graph_degree = deserialize_scalar(res, is); auto metric = deserialize_scalar(res, is); - auto dataset = raft::make_host_matrix(n_rows, dim); - auto graph = raft::make_host_matrix(n_rows, graph_degree); + auto graph = raft::make_host_matrix(n_rows, graph_degree); deserialize_mdspan(res, is, graph.view()); bool has_dataset = deserialize_scalar(res, is); - if (has_dataset) { deserialize_mdspan(res, is, dataset.view()); } - - return index( - res, metric, raft::make_const_mdspan(dataset.view()), raft::make_const_mdspan(graph.view())); + if (has_dataset) { + auto dataset = raft::make_host_matrix(n_rows, dim); + deserialize_mdspan(res, is, dataset.view()); + return index( + res, metric, raft::make_const_mdspan(dataset.view()), raft::make_const_mdspan(graph.view())); + } else { + // create a new index with no dataset - the user must supply via update_dataset themselves + // later (this avoids allocating GPU memory in the meantime) + index idx(res, metric); + idx.update_graph(res, raft::make_const_mdspan(graph.view())); + return idx; + } } template