/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #ifndef HL_SPARSE_H_ #define HL_SPARSE_H_ #include "hl_base.h" /** * @brief Malloc a sparse matrix. * * @param[out] A_d sparse matrix. * @param[in] format format. * @param[in] value_type valueType. * @param[in] dimM height. * @param[in] dimN width. * @param[in] nnz number of none zero element. * */ extern void hl_malloc_sparse_matrix(hl_sparse_matrix_s *A_d, hl_matrix_format_t format, hl_matrix_value_t value_type, int dimM, int dimN, int nnz); /** * @brief Free a sparse matrix. * * @param[in] A_d GPU sparse matrix. * */ extern void hl_free_sparse_matrix(hl_sparse_matrix_s A_d); /** * @brief Construct a sparse matrix use input gpu memory. * * @param[out] A_d sparse matrix. * @param[in] dest_d gpu memory. * @param[in] size size of dest_d. * @param[in] format format. * @param[in] value_type valueType. * @param[in] dimM height. * @param[in] dimN width. * @param[in] nnz number of none zero element. * * @note Destruct api is hl_destruct_sparse_matrix. * */ extern void hl_construct_sparse_matrix(hl_sparse_matrix_s *A_d, void *dest_d, size_t size, hl_matrix_format_t format, hl_matrix_value_t value_type, int dimM, int dimN, int nnz); /** * @brief Use three arrays to construct sparse matrix. * * if format is HL_SPARSE_CSR, size of rows_d is dimM + 1, * and size of cols_d is nnz; * * if format is HL_SPARSE_CSC, size of rows_d is nnz, and size of * cols_d is dimN + 1. * * if valueType is HL_NO_VALUE, size of value_d is zero, * else size of value_d is nnz. * * @param[out] A_d sparse matrix. * @param[in] value_d value. * @param[in] rows_d row. * @param[in] cols_d col. * @param[in] format format. * @param[in] value_type valueType. * @param[in] dimM height. * @param[in] dimN width. * @param[in] nnz number of none zero element. * * @note The corresponding destructor interface is hl_destruct_sparse_matrix. * */ extern void hl_construct_sparse_matrix(hl_sparse_matrix_s *A_d, real *value_d, int *rows_d, int *cols_d, hl_matrix_format_t format, hl_matrix_value_t value_type, int dimM, int dimN, int nnz); /** * @brief Destruct sparse matrix. * * @param[in] A_d sparse matrix. * */ extern void hl_destruct_sparse_matrix(hl_sparse_matrix_s A_d); /** * @brief Copy value & index to sparse matrix. * * if csr_matrix is HL_FLOAT_VALUE. * * 1. csr_val, csr_row, csr_col three pointers are not null. * * 2. csr_val is not null, csr_row adn csr_col are null. * * if csr_matrix is HL_NO_VALUE. * * 1. csr_val will be ignore, csr_row and csr_col are not null. * * * @param[in,out] csr_matrix sparse matrix. * @param[in] csr_val point to csr value array(nnz). * @param[in] csr_row point to csr row indices array(dimM+1). * @param[in] csr_col point to csr col indices array(nnz). * @param[in] stream hl_stream_t type. * */ extern void hl_memcpy_csr_matrix(hl_sparse_matrix_s csr_matrix, real *csr_val, int *csr_row, int *csr_col, hl_stream_t stream); /** * @brief Copy value & index to sparse matrix. * * if csr_matrix is HL_FLOAT_VALUE. * * 1. csc_val, csc_row, csc_col three pointers are not null. * * 2. csc_val is not null, csc_row and csc_col are null. * * if csr_matrix is HL_NO_VALUE. * * 1. csc_val will be ignore, csc_row and csc_col are not null. * * @param[in,out] csc_matrix sparse matrix. * @param[in] csc_val point to csc value array(nnz). * @param[in] csc_row point to csc row indices array(nnz). * @param[in] csc_col point to csc col indices array(dimN+1). * @param[in] stream hl_stream_t type. * * */ extern void hl_memcpy_csc_matrix(hl_sparse_matrix_s csc_matrix, real *csc_val, int *csc_row, int *csc_col, hl_stream_t stream); /** * @brief Copy sparse matrix to sparse matrix. * * @param[out] dst sparse matrix. * @param[in] src sparse matrix. * @param[in] stream hl_stream_t type. * * * @note 1. Format of the src matrix and dst matrix needs to be consistent. * 2. Source matrix has value, the destination matrix has value or * no value can be; the source matrix is no value, then the * destination matrix must also be no value; */ extern void hl_memcpy_sparse_matrix(hl_sparse_matrix_s dst, hl_sparse_matrix_s src, hl_stream_t stream); /** * @brief csr matrix to dense matrix. * * @param[in] A_d csr matrix. * @param[out] C_d dense matrix. * @param[in] dimM height. * @param[in] dimN width. * */ extern void hl_matrix_csr2dense(hl_sparse_matrix_s A_d, real *C_d, int dimM, int dimN); /** * @brief csc matrix to dense matrix. * * @param[in] A_d csc matrix. * @param[out] C_d dense matrix. * @param[in] dimM height. * @param[in] dimN width. * */ extern void hl_matrix_csc2dense(hl_sparse_matrix_s A_d, real *C_d, int dimM, int dimN); /** * @brief C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d. * * @param[in] A_d csr sparse matrix. * @param[in] transa operation op(A) that is non-or transpose. * @param[in] B_d dense matrix. * @param[in] transb operation op(B) that is non-or transpose. * @param[out] C_d dense matrix. * @param[in] dimM matrix height of op(A) & C * @param[in] dimN matrix width of op(B) & C * @param[in] dimK width of op(A) & height of op(B) * @param[in] alpha scalar used for multiplication. * @param[in] beta scalar used for multiplication. * If beta is zero, C does not have to be a valid input. * * @note transb is not support HPPL_OP_T. * */ extern void hl_matrix_csr_mul_dense(hl_sparse_matrix_s A_d, hl_trans_op_t transa, real *B_d, hl_trans_op_t transb, real *C_d, int dimM, int dimN, int dimK, real alpha, real beta); /** * @brief C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d. * * @param[in] A_d sparse matrix. * @param[in] transa operation op(A) that is non-or transpose. * @param[in] B_d dense matrix. * @param[in] transb operation op(B) that is non-or transpose. * @param[out] C_d dense matrix. * @param[in] dimM matrix height of op(A) & C * @param[in] dimN matrix width of op(B) & C * @param[in] dimK width of op(A) & height of op(B) * @param[in] alpha scalar used for multiplication. * @param[in] beta scalar used for multiplication. * If beta is zero, C does not have to be a valid input. * * @note transb is not support HPPL_OP_T. * */ extern void hl_matrix_csc_mul_dense(hl_sparse_matrix_s A_d, hl_trans_op_t transa, real *B_d, hl_trans_op_t transb, real *C_d, int dimM, int dimN, int dimK, real alpha, real beta); /** * @brief C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d. * * @param[in] A_d dense matrix. * @param[in] transa operation op(A) that is non-or transpose. * @param[in] B_d csc sparse matrix. * @param[in] transb operation op(B) that is non-or transpose. * @param[out] C_d dense matrix. * @param[in] dimM matrix height of op(A) & C * @param[in] dimN matrix width of op(B) & C * @param[in] dimK width of op(A) & height of op(B) * @param[in] alpha scalar used for multiplication. * @param[in] beta scalar used for multiplication. * If beta is zero, C does not have to be a valid input. * * @note transa is not support HPPL_OP_T. * */ extern void hl_matrix_dense_mul_csc(real *A_d, hl_trans_op_t transa, hl_sparse_matrix_s B_d, hl_trans_op_t transb, real *C_d, int dimM, int dimN, int dimK, real alpha, real beta); /** * @brief C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d. * Calculated based on the non-zero elements of the matrix C. * * @param[in] A_d dense matrix. * @param[in] transa operation op(A) that is non-or transpose. * @param[in] B_d dense matrix. * @param[in] transb operation op(B) that is non-or transpose. * @param[in,out] C_d sparse matrix. * @param[in] dimM matrix height of op(A) & C * @param[in] dimN matrix width of op(B) & C * @param[in] dimK width of op(A) & height of op(B) * @param[in] alpha scalar used for multiplication. * @param[in] beta scalar used for multiplication. * * @note transb is not support HPPL_OP_T. * */ extern void hl_sparse_matrix_mul(real *A_d, hl_trans_op_t transa, real *B_d, hl_trans_op_t transb, hl_sparse_matrix_s C_d, int dimM, int dimN, int dimK, real alpha, real beta); /** * @brief C_d = alpha*(op(A_d) * op(B_d)) + beta*C_d * * @param[in] A_d dense matrix. * @param[in] transa operation op(A) that is non-or transpose. * @param[in] B_d sparse matrix. * @param[in] transb operation op(B) that is non-or transpose. * @param[out] C_d dense matrix. * @param[in] dimM matrix height of op(A) & C * @param[in] dimN matrix width of op(B) & C * @param[in] dimK width of op(A) & height of op(B) * @param[in] alpha scalar used for multiplication. * @param[in] beta scalar used for multiplication. * If beta is zero, C does not have to be a valid input. * * * @note transa is not support HPPL_OP_T. * */ extern void hl_matrix_dense_mul_csr(real *A_d, hl_trans_op_t transa, hl_sparse_matrix_s B_d, hl_trans_op_t transb, real *C_d, int dimM, int dimN, int dimK, real alpha, real beta); /** * @brief Memcpy csc_matrix to host. * * a. according to csc_matrix, update three arrays * * 1. csc_val, csc_row, csc_col are dest Address. * * 2. if type of csc_matrix is HL_NO_VALUE, update csc_row and csc_col * * 3. if type of csc_matrix is HL_FLOAT_VALUE, update csc_row, * csc_col and csc_value. * * b. The interface is asynchronous copy. To ensure that the data is copied * please call the synchronous interface; * * * @param[out] csc_val point to csc value array(nnz). * @param[in] val_size csc value size. * @param[out] csc_row point to csc row indices array(nnz). * @param[in] row_size csc row size. * @param[out] csc_col point to csc col indices array(dimN + 1). * @param[in] col_size csc column size. * @param[in] csc_matrix sparse matrix. * @param[in] stream hl_stream_t type. * */ extern void hl_memcpy_from_csc_matrix(real *csc_val, size_t val_size, int *csc_row, size_t row_size, int *csc_col, size_t col_size, hl_sparse_matrix_s csc_matrix, hl_stream_t stream); /** * @brief Memcpy sparse matrix to host. * * a. according to csr_matrix, update three arrays * * 1. csr_val, csr_row, csr_col are dest Address. * * 2. if type of csr_matrix is HL_NO_VALUE, update csr_row and csr_col * * 3. if type of csr_matrix is HL_FLOAT_VALUE, update csr_row, * csr_col and csr_value * * b. The interface is asynchronous copy. To ensure that the data is copied * please call the synchronous interface; * * @param[out] csr_val point to csr value array(nnz). * @param[in] val_size csr value size. * @param[out] csr_row point to csr row indices array(nnz). * @param[in] row_size csr row size. * @param[out] csr_col point to csr col indices array(dimN + 1). * @param[in] col_size csr column size. * @param[in] csr_matrix sparse matrix. * @param[in] stream hl_stream_t type. * */ extern void hl_memcpy_from_csr_matrix(real *csr_val, size_t val_size, int *csr_row, size_t row_size, int *csr_col, size_t col_size, hl_sparse_matrix_s csr_matrix, hl_stream_t stream); /** * @brief A_d[j] += B_d[i,j] for i in range(height) * * @param[in,out] A_d vector, size = width. * @param[in] B_d sparse matrix. * @param[in] dimM height. * @param[in] dimN width. * @param[in] scale scale of B_d * */ extern void hl_sparse_matrix_column_sum( real *A_d, hl_sparse_matrix_s B_d, int dimM, int dimN, real scale); /** * @brief implementation of csr sparse matrix in hl_sparse_matirx_column_sum */ extern void hl_matrix_csr_column_sum( real *A_d, hl_sparse_matrix_s B_d, int dimM, int dimN, real scale); /** * @brief A_d[i,j] += B_d[j] * * @param[in,out] A_d sprare matrix. * @param[in] B_d vector, size = A_d.width. * @param[in] scale scale of B_d. * */ extern void hl_sparse_matrix_add_bias(hl_sparse_matrix_s A_d, real *B_d, real scale); /** * @brief implementation of csr sparse matrix in hl_sparse_matrix_add_bias */ extern void hl_matrix_csr_add_bias(hl_sparse_matrix_s A_d, real *B_d, real scale); /** * @brief sparseMatrix = alpha * denseMatrix + beta *sparseMatrix * A_d[i,j] = alpha * B_d[i,j] + beta * A_d[i,j] * Only add value of same (row, col) index in dense matrix and * do not use others values whoes postions are not in sparse matirx. * * @param[in,out] A_d sprare matrix. * @param[in] B_d dense matrix. * @param[in] dimM height of B_d. * @param[in] dimN width of B_d. * @param[in] alpha scale of B_d. * @param[in] beta scale of A_d. * */ extern void hl_sparse_matrix_add_dense(hl_sparse_matrix_s A_d, real *B_d, int dimM, int dimN, real alpha, real beta); /** * @brief implementation of csr sparse matrix in hl_sparse_matrix_add_dense */ extern void hl_matrix_csr_add_dense(hl_sparse_matrix_s A_d, real *B_d, int dimM, int dimN, real alpha, real beta); /** * @brief get rows pionter of GpuSparseMatrix * * @param[in] sMat sparse matrix * * @return return rows pointer, which is gpu address * */ extern int *hl_sparse_matrix_get_rows(hl_sparse_matrix_s sMat); /** * @brief get cols pionter of GpuSparseMatrix * * @param[in] sMat sparse matrix * * @return return cols pointer, which is gpu address * */ extern int *hl_sparse_matrix_get_cols(hl_sparse_matrix_s sMat); /** * @brief get value pionter of GpuSparseMatrix * * @param[in] sMat sparse matrix * * @return return value pointer, which is gpu address * */ extern real *hl_sparse_matrix_get_value(hl_sparse_matrix_s sMat); #endif /* HL_SPARSE_H_ */