Define API for MG random walk

cpp/CMakeLists.txt

@@ -195,6 +195,8 @@ set(CUGRAPH_SOURCES
     src/community/legacy/extract_subgraph_by_vertex.cu
     src/community/legacy/egonet.cu
     src/sampling/random_walks.cu
+    src/sampling/random_walks_sg.cu
+    src/sampling/random_walks_mg.cu
     src/sampling/detail/sampling_utils_mg.cu
     src/sampling/detail/sampling_utils_sg.cu
     src/sampling/uniform_neighbor_sampling_mg.cpp

cpp/include/cugraph/algorithms.hpp

@@ -1350,6 +1350,136 @@ random_walks(raft::handle_t const& handle,
              bool use_padding                                     = false,
              std::unique_ptr<sampling_params_t> sampling_strategy = nullptr);
 
+/**
+ * @brief returns uniform random walks from starting sources, where each path is of given
+ * maximum length.
+ *
+ * @p start_vertices can contain duplicates, in which case different random walks will
+ * be generated for each instance.
+ *
+ * If the graph is weighted, the return contains edge weights.  If the graph is unweighted then
+ * the returned value will be std::nullopt.
+ *
+ * @tparam vertex_t Type of vertex identifiers. Needs to be an integral type.
+ * @tparam edge_t Type of edge identifiers. Needs to be an integral type.
+ * @tparam weight_t Type of edge weights. Needs to be a floating point type.
+ * @tparam multi_gpu Flag indicating whether template instantiation should target single-GPU (false)
+ * @param handle RAFT handle object to encapsulate resources (e.g. CUDA stream, communicator, and
+ * handles to various CUDA libraries) to run graph algorithms.
+ * @param graph_view graph view to operate on
+ * @param start_vertices Device span defining the starting vertices
+ * @param max_length maximum length of random walk
+ * @param seed (optional, defaults to system time), seed for random number generation
+ * @return tuple containing device vectors of vertices and the edge weights (if
+ *         the graph is weighted)<br>
+ *         For each input selector there will be (max_length+1) elements in the
+ *         vertex vector with the starting vertex followed by the subsequent
+ *         vertices in the random walk.  If a path terminates before max_length,
+ *         the vertices will be populated with invalid_vertex_id
+ *         (-1 for signed vertex_t, std::numeric_limits<vertex_t>::max() for an
+ *         unsigned vertex_t type)<br>
+ *         For each input selector there will be max_length elements in the weights
+ *         vector with the edge weight for the edge in the path.  If a path
+ *         terminates before max_length the subsequent edge weights will be
+ *         set to weight_t{0}.
+ */
+// FIXME: Do I care about transposed or not?  I want to be able to operate in either
+// direction.
+template <typename vertex_t, typename edge_t, typename weight_t, bool multi_gpu>
+std::tuple<rmm::device_uvector<vertex_t>, std::optional<rmm::device_uvector<weight_t>>>
+uniform_random_walks(raft::handle_t const& handle,
+                     graph_view_t<vertex_t, edge_t, weight_t, false, multi_gpu> const& graph_view,
+                     raft::device_span<vertex_t const> start_vertices,
+                     size_t max_length,
+                     uint64_t seed = std::numeric_limits<uint64_t>::max());
+
+/**
+ * @brief returns biased random walks from starting sources, where each path is of given
+ * maximum length.
+ *
+ * The next vertex is biased based on the edge weights.  The probability of traversing a
+ * departing edge will be the edge weight divided by the sum of the departing edge weights.
+ *
+ * @p start_vertices can contain duplicates, in which case different random walks will
+ * be generated for each instance.
+ *
+ * @throws                 cugraph::logic_error if the graph is unweighted
+ *
+ * @tparam vertex_t Type of vertex identifiers. Needs to be an integral type.
+ * @tparam edge_t Type of edge identifiers. Needs to be an integral type.
+ * @tparam weight_t Type of edge weights. Needs to be a floating point type.
+ * @tparam multi_gpu Flag indicating whether template instantiation should target single-GPU (false)
+ * @param handle RAFT handle object to encapsulate resources (e.g. CUDA stream, communicator, and
+ * handles to various CUDA libraries) to run graph algorithms.
+ * @param graph_view graph view to operate on
+ * @param start_vertices Device span defining the starting vertices
+ * @param max_length maximum length of random walk
+ * @param seed (optional, defaults to system time), seed for random number generation
+ * @return tuple containing device vectors of vertices and the edge weights<br>
+ *         For each input selector there will be (max_length+1) elements in the
+ *         vertex vector with the starting vertex followed by the subsequent
+ *         vertices in the random walk.  If a path terminates before max_length,
+ *         the vertices will be populated with invalid_vertex_id
+ *         (-1 for signed vertex_t, std::numeric_limits<vertex_t>::max() for an
+ *         unsigned vertex_t type)<br>
+ *         For each input selector there will be max_length elements in the weights
+ *         vector with the edge weight for the edge in the path.  If a path
+ *         terminates before max_length the subsequent edge weights will be
+ *         set to weight_t{0}.
+ */
+template <typename vertex_t, typename edge_t, typename weight_t, bool multi_gpu>
+std::tuple<rmm::device_uvector<vertex_t>, std::optional<rmm::device_uvector<weight_t>>>
+biased_random_walks(raft::handle_t const& handle,
+                    graph_view_t<vertex_t, edge_t, weight_t, false, multi_gpu> const& graph_view,
+                    raft::device_span<vertex_t const> start_vertices,
+                    size_t max_length,
+                    uint64_t seed = std::numeric_limits<uint64_t>::max());
+
+/**
+ * @brief returns biased random walks with node2vec biases from starting sources,
+ * where each path is of given maximum length.
+ *
+ * @p start_vertices can contain duplicates, in which case different random walks will
+ * be generated for each instance.
+ *
+ * If the graph is weighted, the return contains edge weights and the node2vec computation
+ * will utilize the edge weights.  If the graph is unweighted then the return will not contain
+ * edge weights and the node2vec computation will assume an edge weight of 1 for all edges.
+ *
+ * @tparam vertex_t Type of vertex identifiers. Needs to be an integral type.
+ * @tparam edge_t Type of edge identifiers. Needs to be an integral type.
+ * @tparam weight_t Type of edge weights. Needs to be a floating point type.
+ * @tparam multi_gpu Flag indicating whether template instantiation should target single-GPU (false)
+ * @param handle RAFT handle object to encapsulate resources (e.g. CUDA stream, communicator, and
+ * handles to various CUDA libraries) to run graph algorithms.
+ * @param graph_view graph view to operate on
+ * @param start_vertices Device span defining the starting vertices
+ * @param max_length maximum length of random walk
+ * @param p node2vec return parameter
+ * @param q node2vec in-out parameter
+ * @param seed (optional, defaults to system time), seed for random number generation
+ * @return tuple containing device vectors of vertices and the edge weights<br>
+ *         For each input selector there will be (max_length+1) elements in the
+ *         vertex vector with the starting vertex followed by the subsequent
+ *         vertices in the random walk.  If a path terminates before max_length,
+ *         the vertices will be populated with invalid_vertex_id
+ *         (-1 for signed vertex_t, std::numeric_limits<vertex_t>::max() for an
+ *         unsigned vertex_t type)<br>
+ *         For each input selector there will be max_length elements in the weights
+ *         vector with the edge weight for the edge in the path.  If a path
+ *         terminates before max_length the subsequent edge weights will be
+ *         set to weight_t{0}.
+ */
+template <typename vertex_t, typename edge_t, typename weight_t, bool multi_gpu>
+std::tuple<rmm::device_uvector<vertex_t>, std::optional<rmm::device_uvector<weight_t>>>
+node2vec_random_walks(raft::handle_t const& handle,
+                      graph_view_t<vertex_t, edge_t, weight_t, false, multi_gpu> const& graph_view,
+                      raft::device_span<vertex_t const> start_vertices,
+                      size_t max_length,
+                      weight_t p,
+                      weight_t q,
+                      uint64_t seed = std::numeric_limits<uint64_t>::max());
+
 #ifndef NO_CUGRAPH_OPS
 /**
  * @brief generate sub-sampled graph as an adjacency list (CSR format) given input graph,

cpp/include/cugraph_c/sampling_algorithms.h

@@ -36,8 +36,78 @@ typedef struct {
   int32_t align_;
 } cugraph_random_walk_result_t;
 
+/**
+ * @brief  Compute uniform random walks
+ *
+ * @param [in]  handle          Handle for accessing resources
+ * @param [in]  graph           Pointer to graph.  NOTE: Graph might be modified if the storage
+ *                              needs to be transposed
+ * @param [in]  start_vertices  Array of source vertices
+ * @param [in]  max_length      Maximum length of the generated path
+ * @param [in]  result          Output from the node2vec call
+ * @param [out] error           Pointer to an error object storing details of any error.  Will
+ *                              be populated if error code is not CUGRAPH_SUCCESS
+ * @return error code
+ */
+cugraph_error_code_t cugraph_uniform_random_walks(
+  const cugraph_resource_handle_t* handle,
+  cugraph_graph_t* graph,
+  const cugraph_type_erased_device_array_view_t* start_vertices,
+  size_t max_length,
+  cugraph_random_walk_result_t** result,
+  cugraph_error_t** error);
+
+/**
+ * @brief  Compute biased random walks
+ *
+ * @param [in]  handle          Handle for accessing resources
+ * @param [in]  graph           Pointer to graph.  NOTE: Graph might be modified if the storage
+ *                              needs to be transposed
+ * @param [in]  start_vertices  Array of source vertices
+ * @param [in]  max_length      Maximum length of the generated path
+ * @param [in]  result          Output from the node2vec call
+ * @param [out] error           Pointer to an error object storing details of any error.  Will
+ *                              be populated if error code is not CUGRAPH_SUCCESS
+ * @return error code
+ */
+cugraph_error_code_t cugraph_biased_random_walks(
+  const cugraph_resource_handle_t* handle,
+  cugraph_graph_t* graph,
+  const cugraph_type_erased_device_array_view_t* start_vertices,
+  size_t max_length,
+  cugraph_random_walk_result_t** result,
+  cugraph_error_t** error);
+
+/**
+ * @brief  Compute random walks using the node2vec framework.
+ *
+ * @param [in]  handle          Handle for accessing resources
+ * @param [in]  graph           Pointer to graph.  NOTE: Graph might be modified if the storage
+ *                              needs to be transposed
+ * @param [in]  start_vertices  Array of source vertices
+ * @param [in]  max_length      Maximum length of the generated path
+ * @param [in]  compress_result If true, return the paths as a compressed sparse row matrix,
+ *                              otherwise return as a dense matrix
+ * @param [in]  p               The return parameter
+ * @param [in]  q               The in/out parameter
+ * @param [in]  result          Output from the node2vec call
+ * @param [out] error           Pointer to an error object storing details of any error.  Will
+ *                              be populated if error code is not CUGRAPH_SUCCESS
+ * @return error code
+ */
+cugraph_error_code_t cugraph_node2vec_random_walks(
+  const cugraph_resource_handle_t* handle,
+  cugraph_graph_t* graph,
+  const cugraph_type_erased_device_array_view_t* start_vertices,
+  size_t max_length,
+  double p,
+  double q,
+  cugraph_random_walk_result_t** result,
+  cugraph_error_t** error);
+
 /**
  * @brief  Compute random walks using the node2vec framework.
+ * @deprecated This call should be replaced with cugraph_node2vec_random_walks
  *
  * @param [in]  handle       Handle for accessing resources
  * @param [in]  graph        Pointer to graph.  NOTE: Graph might be modified if the storage
@@ -94,6 +164,7 @@ cugraph_type_erased_device_array_view_t* cugraph_random_walk_result_get_weights(
 
 /**
  * @brief     If the random walk result is compressed, get the path sizes
+ * @deprecated This call will no longer be relevant once the new node2vec are called
  *
  * @param [in]   result   The result from a random walk algorithm
  * @return type erased array pointing to the path sizes in device memory