/*! \file */ /* ************************************************************************ * Copyright (C) 2026 Advanced Micro Devices, Inc. All rights Reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. * * ************************************************************************ */ #include "testing_spilu0.hpp" #include "rocsparse_clients_objects.hpp" #include "rocsparse_clients_spmat_descr.hpp" #include "rocsparse_enum.hpp" #include "testing.hpp" #include namespace rocsparse_clients { class spilu0_descr { private: rocsparse_handle m_handle{}; rocsparse_spilu0_descr m_descr{}; public: struct config { rocsparse_spilu0_alg alg{}; rocsparse_analysis_policy analysis_policy{}; rocsparse_datatype compute_datatype{}; rocsparse_pointer_mode singular_pivot_tolerance_pointer_mode{}; const void* singular_pivot_tolerance{}; const int32_t boost_enable{}; rocsparse_pointer_mode boost_val_pointer_mode{}; const void* boost_val{}; rocsparse_pointer_mode boost_tolerance_pointer_mode{}; const void* boost_tolerance{}; }; protected: config* m_config; public: const config* get_config() const { return this->m_config; } host_dense_vector m_cpu_symbolic_singularity_position{}; host_dense_vector m_cpu_numeric_exact_singularity_position{}; host_dense_vector m_cpu_numeric_near_singularity_position{}; host_dense_vector m_host_symbolic_singularity_position{}; host_dense_vector m_host_numeric_singularity_position{}; device_dense_vector m_device_symbolic_singularity_position{}; device_dense_vector m_device_numeric_singularity_position{}; spilu0_descr(rocsparse_handle handle, int64_t batch_count) : m_handle(handle) , m_cpu_symbolic_singularity_position(batch_count) , m_cpu_numeric_exact_singularity_position(batch_count) , m_cpu_numeric_near_singularity_position(batch_count) , m_host_symbolic_singularity_position(batch_count) , m_host_numeric_singularity_position(batch_count) , m_device_symbolic_singularity_position(batch_count) , m_device_numeric_singularity_position(batch_count) { ROCSPARSE_CLIENTS_ROUTINE_TRACE; rocsparse_error* p_error = nullptr; const rocsparse_status status = rocsparse_spilu0_descr_create(handle, &this->m_descr, p_error); if(status != rocsparse_status_success) { throw(status); } } ~spilu0_descr() { ROCSPARSE_CLIENTS_ROUTINE_TRACE; rocsparse_error* p_error = nullptr; std::ignore = rocsparse_spilu0_descr_destroy(this->m_handle, this->m_descr, p_error); } inline operator rocsparse_spilu0_descr&() { return this->m_descr; } inline operator const rocsparse_spilu0_descr&() const { return this->m_descr; } }; } template static inline T host_assign_ilu0_boost_value(const T& value, const T& boost_val) { #ifdef ROCSPARSE_WITH_ILU0_BOOST_SIGN const auto abs_value = std::abs(value); const auto abs_boost = std::abs(boost_val); return (abs_value > 0) ? (static_cast(abs_boost) * (value / abs_value)) : static_cast(abs_boost); #else return boost_val; #endif } template void host_csrilu0(J M, const I* csr_row_ptr, const J* csr_col_ind, T* csr_val, rocsparse_index_base base, int64_t* struct_pivot, int64_t* numeric_pivot, int64_t* singular_pivot, const double* singular_tol, int32_t boost_enable, const floating_data_t* boost_tol, const T* boost_val) { ROCSPARSE_CLIENTS_ROUTINE_TRACE; if((struct_pivot == nullptr) || (numeric_pivot == nullptr) || (singular_pivot == nullptr)) { std::cerr << "host_csrilu0: invalid parameters, failed condition: ((struct_pivot != " "nullptr) && (numeric_pivot != nullptr) && (singular_pivot != nullptr))." << std::endl; throw(1); } // Initialize pivot *struct_pivot = -1; *numeric_pivot = -1; *singular_pivot = -1; // pointer of upper part of each row std::vector diag_offset(M, -1); std::vector nnz_entries(M, 0); // ai = 0 to N loop over all rows for(J ai = 0; ai < M; ++ai) { // ai-th row entries I row_begin = csr_row_ptr[ai] - base; I row_end = csr_row_ptr[ai + 1] - base; I j; // nnz position of ai-th row in val array for(j = row_begin; j < row_end; ++j) { nnz_entries[csr_col_ind[j] - base] = j; } bool has_diag = false; I diag_pos = -1; // loop over ai-th row nnz entries for(j = row_begin; j < row_end; ++j) { // if nnz entry is in lower matrix if(csr_col_ind[j] - base < ai) { J col_j = csr_col_ind[j] - base; I diag_j = diag_offset[col_j]; if(diag_j < 0) continue; T diag_val = csr_val[diag_j]; if(boost_enable) { diag_val = (boost_tol[0] >= std::abs(diag_val)) ? host_assign_ilu0_boost_value(diag_val, boost_val[0]) : diag_val; csr_val[diag_j] = diag_val; } else { // Check for numeric singular pivot if(std::abs(diag_val) <= singular_tol[0]) { *singular_pivot = (*singular_pivot == -1) ? (col_j + base) : std::min(*singular_pivot, int64_t(col_j + base)); } // Check for numeric zero pivot if(diag_val == static_cast(0)) { *numeric_pivot = (*numeric_pivot == -1) ? (col_j + base) : std::min(*numeric_pivot, int64_t(col_j + base)); continue; } } { // multiplication factor csr_val[j] = csr_val[j] / diag_val; // loop over upper offset pointer and do linear combination for nnz entry for(I k = diag_j + 1; k < csr_row_ptr[col_j + 1] - base; ++k) { // if nnz at this position do linear combination if(nnz_entries[csr_col_ind[k] - base] != 0) { I idx = nnz_entries[csr_col_ind[k] - base]; csr_val[idx] = std::fma(-csr_val[j], csr_val[k], csr_val[idx]); } } } } else if(csr_col_ind[j] - base == ai) { has_diag = true; diag_pos = j; break; } else { break; } } if(!has_diag) { // Structural (and numerical) zero diagonal *struct_pivot = (*struct_pivot == -1) ? (ai + base) : std::min(*struct_pivot, int64_t(ai + base)); *numeric_pivot = (*numeric_pivot == -1) ? (ai + base) : std::min(*numeric_pivot, int64_t(ai + base)); } else { // set diagonal pointer to diagonal element diag_offset[ai] = diag_pos; if(boost_enable) { if(std::abs(csr_val[diag_pos]) <= boost_tol[0]) { csr_val[diag_pos] = host_assign_ilu0_boost_value(csr_val[diag_pos], boost_val[0]); } } else { const I diag_pos = diag_offset[ai]; const bool is_diag = (diag_pos >= 0) && (csr_col_ind[diag_pos] == (ai + base)); const bool is_singular_diag = is_diag && (std::abs(csr_val[diag_pos]) <= singular_tol[0]); const bool is_zero_diag = is_diag && (csr_val[diag_pos] == static_cast(0)); // check for singular diagonal if(is_singular_diag) { *singular_pivot = (*singular_pivot == -1) ? (ai + base) : std::min(*singular_pivot, int64_t(ai + base)); } // check for zero diagonal if(is_zero_diag) { *numeric_pivot = (*numeric_pivot == -1) ? (ai + base) : std::min(*numeric_pivot, int64_t(ai + base)); } } // clear nnz entries for(j = row_begin; j < row_end; ++j) { nnz_entries[csr_col_ind[j] - base] = 0; } } } if(*struct_pivot != -1) { *numeric_pivot = (*numeric_pivot == -1) ? (*struct_pivot) : std::min(*numeric_pivot, *struct_pivot); } if(*numeric_pivot != -1) { *singular_pivot = (*singular_pivot == -1) ? (*numeric_pivot) : std::min(*singular_pivot, *numeric_pivot); } } template void host_bsrilu0(rocsparse_direction dir, J mb, const I* bsr_row_ptr, const J* bsr_col_ind, T* bsr_val, J bsr_dim, rocsparse_index_base base, int64_t* struct_pivot, int64_t* numeric_pivot, int32_t boost_enable, const floating_data_t* boost_tol, const T* boost_val) { ROCSPARSE_CLIENTS_ROUTINE_TRACE; // Initialize pivots *struct_pivot = mb + 1; *numeric_pivot = mb + 1; // Temporary vector to hold diagonal offset to access diagonal BSR block std::vector diag_offset(mb); std::vector nnz_entries(mb, -1); if(mb > 0) { // First diagonal block is index 0 diag_offset[0] = 0; } // Loop over all BSR rows for(J i = 0; i < mb; ++i) { // Flag whether we have a diagonal block or not bool has_diag = false; // BSR column entry and exit point I row_begin = bsr_row_ptr[i] - base; I row_end = bsr_row_ptr[i + 1] - base; I j; // Set up entry points for linear combination for(j = row_begin; j < row_end; ++j) { J col_j = bsr_col_ind[j] - base; nnz_entries[col_j] = j; } // Process lower diagonal BSR blocks (diagonal BSR block is excluded) for(j = row_begin; j < row_end; ++j) { // Column index of current BSR block J bsr_col = bsr_col_ind[j] - base; // If this is a diagonal block, set diagonal flag to true and skip // all upcoming blocks as we exceed the lower matrix part if(bsr_col == i) { has_diag = true; break; } // Skip all upper matrix blocks if(bsr_col > i) { break; } // Process all lower matrix BSR blocks // Obtain corresponding row entry and exit point that corresponds with the // current BSR column. Actually, we skip all lower matrix column indices, // therefore starting with the diagonal entry. I diag_j = diag_offset[bsr_col]; I row_end_j = bsr_row_ptr[bsr_col + 1] - base; // Loop through all rows within the BSR block for(J bi = 0; bi < bsr_dim; ++bi) { T diag = bsr_val[BSR_IND(diag_j, bi, bi, dir)]; // Process all rows within the BSR block for(J bk = 0; bk < bsr_dim; ++bk) { T val = bsr_val[BSR_IND(j, bk, bi, dir)]; // Multiplication factor bsr_val[BSR_IND(j, bk, bi, dir)] = val /= diag; // Loop through columns of bk-th row and do linear combination for(J bj = bi + 1; bj < bsr_dim; ++bj) { bsr_val[BSR_IND(j, bk, bj, dir)] = std::fma(-val, bsr_val[BSR_IND(diag_j, bi, bj, dir)], bsr_val[BSR_IND(j, bk, bj, dir)]); } } } // Loop over upper offset pointer and do linear combination for nnz entry for(I k = diag_j + 1; k < row_end_j; ++k) { J bsr_col_k = bsr_col_ind[k] - base; if(nnz_entries[bsr_col_k] != -1) { J m = nnz_entries[bsr_col_k]; // Loop through all rows within the BSR block for(J bi = 0; bi < bsr_dim; ++bi) { // Loop through columns of bi-th row and do linear combination for(J bj = 0; bj < bsr_dim; ++bj) { T sum = static_cast(0); for(J bk = 0; bk < bsr_dim; ++bk) { sum = std::fma(bsr_val[BSR_IND(j, bi, bk, dir)], bsr_val[BSR_IND(k, bk, bj, dir)], sum); } bsr_val[BSR_IND(m, bi, bj, dir)] -= sum; } } } } } // Check for structural pivot if(!has_diag) { *struct_pivot = std::min(*struct_pivot, int64_t(i + base)); break; } // Process diagonal if(bsr_col_ind[j] - base == i) { // Loop through all rows within the BSR block for(J bi = 0; bi < bsr_dim; ++bi) { T diag = bsr_val[BSR_IND(j, bi, bi, dir)]; if(boost_enable) { diag = (boost_tol[0] >= std::abs(diag)) ? host_assign_ilu0_boost_value(diag, boost_val[0]) : diag; bsr_val[BSR_IND(j, bi, bi, dir)] = diag; } else { // Check for numeric pivot if(diag == static_cast(0)) { *numeric_pivot = std::min(*numeric_pivot, int64_t(bsr_col_ind[j])); continue; } } // Process all rows within the BSR block after bi-th row for(J bk = bi + 1; bk < bsr_dim; ++bk) { T val = bsr_val[BSR_IND(j, bk, bi, dir)]; // Multiplication factor bsr_val[BSR_IND(j, bk, bi, dir)] = val /= diag; // Loop through remaining columns of bk-th row and do linear combination for(J bj = bi + 1; bj < bsr_dim; ++bj) { bsr_val[BSR_IND(j, bk, bj, dir)] = std::fma(-val, bsr_val[BSR_IND(j, bi, bj, dir)], bsr_val[BSR_IND(j, bk, bj, dir)]); } } } } // Store diagonal BSR block entry point I row_diag = diag_offset[i] = j; // Process upper diagonal BSR blocks for(j = row_diag + 1; j < row_end; ++j) { // Loop through all rows within the BSR block for(J bi = 0; bi < bsr_dim; ++bi) { // Process all rows within the BSR block after bi-th row for(J bk = bi + 1; bk < bsr_dim; ++bk) { // Loop through columns of bk-th row and do linear combination for(J bj = 0; bj < bsr_dim; ++bj) { bsr_val[BSR_IND(j, bk, bj, dir)] = std::fma(-bsr_val[BSR_IND(row_diag, bk, bi, dir)], bsr_val[BSR_IND(j, bi, bj, dir)], bsr_val[BSR_IND(j, bk, bj, dir)]); } } } } // Reset entry points for(j = row_begin; j < row_end; ++j) { J col_j = bsr_col_ind[j] - base; nnz_entries[col_j] = -1; } } *struct_pivot = (*struct_pivot == mb + 1) ? -1 : *struct_pivot; *numeric_pivot = (*numeric_pivot == mb + 1) ? -1 : *numeric_pivot; // Solve pivot gives the first numerical or structural non-invertible block if(numeric_pivot[0] == -1) { numeric_pivot[0] = struct_pivot[0]; } else if(struct_pivot[0] != -1) { numeric_pivot[0] = std::min(numeric_pivot[0], struct_pivot[0]); } } template void testing_spilu0_set_input_bad_arg(const Arguments& arg) { rocsparse_error* p_error = nullptr; rocsparse_local_handle local_handle; rocsparse_spilu0_descr spilu0_descr = (rocsparse_spilu0_descr)0x4; rocsparse_handle handle = local_handle; static constexpr int nex = 2; static const int ex[nex] = {4, 5}; const rocsparse_spilu0_input input = rocsparse_spilu0_input_alg; void* data = (void*)0x4; size_t data_size_in_bytes = sizeof(input); select_bad_arg_analysis(rocsparse_spilu0_set_input, nex, ex, handle, //0 spilu0_descr, //1 input, //2 data, //3 data_size_in_bytes, //4 p_error); // 5 CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_descr_create(handle, &spilu0_descr, p_error)); for(auto e : {rocsparse_spilu0_input_alg, rocsparse_spilu0_input_analysis_policy, rocsparse_spilu0_input_compute_datatype, rocsparse_spilu0_input_boost_enable, rocsparse_spilu0_input_boost_tolerance, rocsparse_spilu0_input_boost_value, rocsparse_spilu0_input_singularity_tolerance}) { switch(e) { case rocsparse_spilu0_input_alg: case rocsparse_spilu0_input_analysis_policy: case rocsparse_spilu0_input_compute_datatype: case rocsparse_spilu0_input_boost_enable: case rocsparse_spilu0_input_boost_tolerance: case rocsparse_spilu0_input_boost_value: case rocsparse_spilu0_input_singularity_tolerance: { EXPECT_ROCSPARSE_STATUS( rocsparse_spilu0_set_input(handle, spilu0_descr, e, data, 0, p_error), rocsparse_status_invalid_value); break; } } } // // Singularity force to be double // EXPECT_ROCSPARSE_STATUS(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, data, sizeof(float), p_error), rocsparse_status_invalid_value); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_descr_destroy(handle, spilu0_descr, p_error)); } template void testing_spilu0_buffer_size_bad_arg(const Arguments& arg) { rocsparse_local_handle local_handle; rocsparse_handle handle = local_handle; rocsparse_spilu0_descr spilu0_descr = (rocsparse_spilu0_descr)0x4; rocsparse_spmat_descr A = (rocsparse_spmat_descr)0x4; rocsparse_spmat_descr P = (rocsparse_spmat_descr)0x4; rocsparse_spilu0_stage spilu0_stage = rocsparse_spilu0_stage_analysis; rocsparse_error* p_error = nullptr; { size_t* p_buffer_size_in_bytes = (size_t*)0x4; #define PARAMS_BUFFER_SIZE handle, spilu0_descr, A, P, spilu0_stage, p_buffer_size_in_bytes, p_error static constexpr int nex = 1; static const int ex[nex] = {6}; select_bad_arg_analysis(rocsparse_spilu0_buffer_size, nex, ex, PARAMS_BUFFER_SIZE); #undef PARAMS_BUFFER_SIZE } } template void testing_spilu0_get_output_bad_arg(const Arguments& arg) { rocsparse_local_handle local_handle; rocsparse_handle handle = local_handle; rocsparse_spilu0_descr spilu0_descr = (rocsparse_spilu0_descr)0x4; rocsparse_error* p_error = nullptr; static constexpr int nex = 2; static const int ex[nex] = {4, 5}; size_t data_size_in_bytes = sizeof(int64_t); void* data = (void*)0x4; rocsparse_spilu0_output output = rocsparse_spilu0_output_singularity_position; select_bad_arg_analysis(rocsparse_spilu0_get_output, nex, ex, handle, spilu0_descr, output, data, data_size_in_bytes, p_error); } template void testing_spilu0_analysis_bad_arg(const Arguments& arg) { rocsparse_local_handle local_handle; rocsparse_handle handle = local_handle; rocsparse_spilu0_descr spilu0_descr = (rocsparse_spilu0_descr)0x4; rocsparse_spmat_descr A = (rocsparse_spmat_descr)0x4; rocsparse_spmat_descr P = (rocsparse_spmat_descr)0x4; rocsparse_spilu0_stage spilu0_stage = rocsparse_spilu0_stage_analysis; void* buffer = (void*)0x4; rocsparse_error* p_error = nullptr; { const size_t buffer_size_in_bytes = 1; #define PARAMS handle, spilu0_descr, A, P, spilu0_stage, buffer_size_in_bytes, buffer, p_error static constexpr int nex = 2; static const int ex[nex] = {5, 7}; select_bad_arg_analysis(rocsparse_spilu0, nex, ex, PARAMS); #undef PARAMS } } template void testing_spilu0_bad_arg(const Arguments& arg) { testing_spilu0_buffer_size_bad_arg(arg); testing_spilu0_analysis_bad_arg(arg); testing_spilu0_set_input_bad_arg(arg); testing_spilu0_get_output_bad_arg(arg); rocsparse_error* p_error = nullptr; rocsparse_local_handle local_handle; rocsparse_handle handle = local_handle; // // Now get a concrete example and continue. // rocsparse_clients::csr_tridiag_matrix_t A(4); rocsparse_spmat_descr P = A; host_scalar hsingularity_tolerance(1); hsingularity_tolerance[0] = 1.0e-5; device_scalar dsingularity_tolerance(hsingularity_tolerance); for(auto analysis_policy : {rocsparse_analysis_policy_force, rocsparse_analysis_policy_reuse}) { rocsparse_clients::spilu0_descr spilu0_descr(handle, 1); const rocsparse_spilu0_alg alg = rocsparse_spilu0_alg_default; const rocsparse_datatype compute_datatype = get_datatype(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input( handle, spilu0_descr, rocsparse_spilu0_input_alg, &alg, sizeof(alg), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_analysis_policy, &analysis_policy, sizeof(analysis_policy), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_compute_datatype, &compute_datatype, sizeof(compute_datatype), p_error)); size_t buffer_size; CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_buffer_size( handle, spilu0_descr, A, P, rocsparse_spilu0_stage_analysis, &buffer_size, p_error)); { device_dense_vector buffer(buffer_size); CHECK_HIP_ERROR(hipMemset(buffer, 255 - 1, buffer_size)); // // Call compute before analysis. // EXPECT_ROCSPARSE_STATUS(rocsparse_status_invalid_value, rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_compute, buffer_size, buffer, p_error)); // // Call analysis. // CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_analysis, buffer_size, buffer, p_error)); for(auto input : {rocsparse_spilu0_input_alg, rocsparse_spilu0_input_analysis_policy, rocsparse_spilu0_input_compute_datatype, rocsparse_spilu0_input_boost_enable, rocsparse_spilu0_input_boost_tolerance, rocsparse_spilu0_input_boost_value, rocsparse_spilu0_input_singularity_tolerance}) { switch(input) { case rocsparse_spilu0_input_alg: case rocsparse_spilu0_input_compute_datatype: case rocsparse_spilu0_input_analysis_policy: { EXPECT_ROCSPARSE_STATUS( rocsparse_status_invalid_value, rocsparse_spilu0_set_input( handle, spilu0_descr, input, (void*)0x4, sizeof(int64_t), p_error)); break; } case rocsparse_spilu0_input_singularity_tolerance: { EXPECT_ROCSPARSE_STATUS( rocsparse_status_invalid_value, rocsparse_spilu0_set_input( handle, spilu0_descr, input, (void*)0x4, sizeof(float), p_error)); CHECK_ROCSPARSE_ERROR( rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, hsingularity_tolerance, sizeof(double), p_error)); CHECK_ROCSPARSE_ERROR( rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, dsingularity_tolerance, sizeof(double), p_error)); break; } case rocsparse_spilu0_input_boost_enable: case rocsparse_spilu0_input_boost_tolerance: case rocsparse_spilu0_input_boost_value: { break; } } } // // Call analysis twice. // EXPECT_ROCSPARSE_STATUS(rocsparse_status_invalid_value, rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_analysis, buffer_size, buffer, p_error)); } { CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_buffer_size( handle, spilu0_descr, A, P, rocsparse_spilu0_stage_compute, &buffer_size, p_error)); device_dense_vector buffer(buffer_size); CHECK_HIP_ERROR(hipMemset(buffer, 255 - 1, buffer_size)); CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, hsingularity_tolerance, sizeof(double), p_error)); // // Call compute. // CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_compute, buffer_size, buffer, p_error)); // // Call analysis after compute. // EXPECT_ROCSPARSE_STATUS(rocsparse_status_invalid_value, rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_analysis, buffer_size, buffer, p_error)); CHECK_ROCSPARSE_ERROR( rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, dsingularity_tolerance, sizeof(double), p_error)); // // Call compute. // CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_compute, buffer_size, buffer, p_error)); // // Call analysis after compute. // EXPECT_ROCSPARSE_STATUS(rocsparse_status_invalid_value, rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_analysis, buffer_size, buffer, p_error)); // // Call compute. // CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, P, rocsparse_spilu0_stage_compute, buffer_size, buffer, p_error)); } } } template void rocsparse_clients_spilu0_host(rocsparse_clients::spilu0_descr& spilu0_descr, rocsparse_clients::spmat_descr& A, const double* singular_pivot_tolerance, int32_t boost_enable, const floating_data_t* boost_tolerance, const T* boost_value) { auto& cpu_symbolic_pivot = spilu0_descr.m_cpu_symbolic_singularity_position; auto& cpu_numeric_near_pivot = spilu0_descr.m_cpu_numeric_near_singularity_position; auto& cpu_numeric_exact_pivot = spilu0_descr.m_cpu_numeric_exact_singularity_position; const rocsparse_format format = A.get_format(); const int64_t batch_count = A.get_batch_count(); switch(format) { case rocsparse_format_csr: { auto& host = A.template as().host(); for(int64_t i = 0; i < batch_count; ++i) { T* p = host.val.data() + i * A.get_stride(); host_csrilu0(host.m, host.ptr, host.ind, p, host.base, cpu_symbolic_pivot + i, cpu_numeric_exact_pivot + i, cpu_numeric_near_pivot + i, singular_pivot_tolerance, boost_enable, boost_tolerance, boost_value); } for(int64_t j = 0; j < batch_count; ++j) { if(cpu_numeric_near_pivot[j] == -1) { cpu_numeric_near_pivot[j] = cpu_numeric_exact_pivot[j]; } else { if(cpu_numeric_exact_pivot[j] != -1) { cpu_numeric_near_pivot[j] = std::min(cpu_numeric_near_pivot[j], cpu_numeric_exact_pivot[j]); } } } break; } case rocsparse_format_bsr: { auto& host = A.template as().host(); for(int64_t i = 0; i < batch_count; ++i) { T* p = host.val.data() + i * A.get_stride(); host_bsrilu0(host.block_direction, host.mb, host.ptr, host.ind, p, host.row_block_dim, host.base, cpu_symbolic_pivot + i, cpu_numeric_exact_pivot + i, boost_enable, boost_tolerance, boost_value); for(int64_t j = 0; j < batch_count; ++j) { cpu_numeric_near_pivot[j] = cpu_numeric_exact_pivot[j]; } } break; } case rocsparse_format_ell: case rocsparse_format_sell: case rocsparse_format_bell: case rocsparse_format_coo: case rocsparse_format_coo_aos: case rocsparse_format_csc: { break; } } } template void testing_spilu0(const Arguments& arg_) { Arguments arg(arg_); rocsparse_error* p_error = nullptr; // // Import matrix. // if(arg.M != arg.N) { return; } static constexpr const bool full_rank = true; int64_t batch_count = arg.batch_count; if(batch_count == -1) batch_count = 1; rocsparse_local_handle handle(arg); hipStream_t stream; CHECK_ROCSPARSE_ERROR(rocsparse_get_stream(handle, &stream)); const double h_singular_pivot_tolerance[1] = {0.001}; const rocsparse_spilu0_alg alg = rocsparse_spilu0_alg_default; const rocsparse_analysis_policy analysis_policy = arg.apol; const rocsparse_datatype compute_datatype = get_datatype(); const int32_t boost_enable = arg.numericboost; const T h_boost_value[1] = {arg.get_boostval()}; const floating_data_t h_boost_tolerance[1] = {static_cast>(arg.boosttol)}; rocsparse_clients::spmat_descr A(arg, batch_count, full_rank); if(false == A.is_square()) { return; } rocsparse_clients::spilu0_descr spilu0_descr(handle, batch_count); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input( handle, spilu0_descr, rocsparse_spilu0_input_alg, &alg, sizeof(alg), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_analysis_policy, &analysis_policy, sizeof(analysis_policy), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_compute_datatype, &compute_datatype, sizeof(compute_datatype), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_boost_enable, &boost_enable, sizeof(compute_datatype), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host)); const T h_boost_val = arg.get_boostval(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_boost_value, &h_boost_val, sizeof(&h_boost_val), p_error)); const double h_boost_tol = static_cast(arg.boosttol); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_boost_tolerance, &h_boost_tol, sizeof(h_boost_tol), p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_set_input(handle, spilu0_descr, rocsparse_spilu0_input_singularity_tolerance, &h_singular_pivot_tolerance, sizeof(double), p_error)); auto& device_symbolic_pivot = spilu0_descr.m_device_symbolic_singularity_position; auto& host_symbolic_pivot = spilu0_descr.m_host_symbolic_singularity_position; { size_t buffer_size_in_bytes = std::numeric_limits::max(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_buffer_size(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_analysis, &buffer_size_in_bytes, p_error)); device_dense_vector buffer(buffer_size_in_bytes); CHECK_HIP_ERROR(hipMemset(buffer, 255 - 1, buffer_size_in_bytes)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_analysis, buffer_size_in_bytes, buffer, p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_get_output(handle, spilu0_descr, rocsparse_spilu0_output_singularity_position, host_symbolic_pivot, sizeof(int64_t), p_error)); CHECK_HIP_ERROR(hipStreamSynchronize(stream)); } auto& device_numeric_pivot = spilu0_descr.m_device_numeric_singularity_position; auto& host_numeric_pivot = spilu0_descr.m_host_numeric_singularity_position; if(arg.unit_check) { CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_get_output(handle, spilu0_descr, rocsparse_spilu0_output_singularity_position, device_symbolic_pivot, sizeof(int64_t), p_error)); CHECK_HIP_ERROR(hipStreamSynchronize(stream)); // // Check pivot is the same with either host or device mode. // host_symbolic_pivot.unit_check(device_symbolic_pivot); // // Check consistency of the status and the symbolic resulting pivot. // // // Perform calculation. // { size_t buffer_size_in_bytes = std::numeric_limits::max(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_buffer_size(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_compute, &buffer_size_in_bytes, p_error)); device_dense_vector buffer(buffer_size_in_bytes); CHECK_HIP_ERROR(hipMemset(buffer, 255 - 1, buffer_size_in_bytes)); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_compute, buffer_size_in_bytes, buffer, p_error)); CHECK_ROCSPARSE_ERROR(rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_host)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_get_output(handle, spilu0_descr, rocsparse_spilu0_output_singularity_position, host_numeric_pivot, sizeof(int64_t), p_error)); CHECK_ROCSPARSE_ERROR( rocsparse_set_pointer_mode(handle, rocsparse_pointer_mode_device)); CHECK_ROCSPARSE_ERROR( rocsparse_spilu0_get_output(handle, spilu0_descr, rocsparse_spilu0_output_singularity_position, device_numeric_pivot, sizeof(int64_t), p_error)); CHECK_HIP_ERROR(hipStreamSynchronize(stream)); // // Check numeric pivots match. // host_numeric_pivot.unit_check(device_numeric_pivot); // // Perform calculation on host. // rocsparse_clients_spilu0_host(spilu0_descr, A, h_singular_pivot_tolerance, boost_enable, h_boost_tolerance, h_boost_value); auto& cpu_symbolic_pivot = spilu0_descr.m_cpu_symbolic_singularity_position; auto& cpu_numeric_near_pivot = spilu0_descr.m_cpu_numeric_near_singularity_position; cpu_symbolic_pivot.unit_check(host_symbolic_pivot); cpu_numeric_near_pivot.unit_check(host_numeric_pivot); A.near_check_values(host_symbolic_pivot, host_numeric_pivot); } } if(arg.timing) { size_t buffer_size_in_bytes = std::numeric_limits::max(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0_buffer_size(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_compute, &buffer_size_in_bytes, p_error)); device_dense_vector buffer(buffer_size_in_bytes); CHECK_HIP_ERROR(hipMemset(buffer, 255 - 1, buffer_size_in_bytes)); const int32_t n_cold_calls = 2; const int32_t n_sub_calls = arg.iters_inner; const int32_t n_calls = arg.iters; hipStream_t stream; rocsparse_get_stream(handle, &stream); for(int32_t iter = 0; iter < n_cold_calls; ++iter) { A.reinit_values(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_compute, buffer_size_in_bytes, buffer, p_error)); CHECK_HIP_ERROR(hipStreamSynchronize(stream)); } std::vector gpu_time(n_calls); rocsparse_clients::timer t(stream); for(int32_t iter = 0; iter < n_calls; ++iter) { gpu_time[iter] = 0; for(int32_t sub_iter = 0; sub_iter < n_sub_calls; ++sub_iter) { A.reinit_values(); t.start(); CHECK_ROCSPARSE_ERROR(rocsparse_spilu0(handle, spilu0_descr, A, A, rocsparse_spilu0_stage_compute, buffer_size_in_bytes, buffer, p_error)); CHECK_HIP_ERROR(hipStreamSynchronize(stream)); const double t_microseconds = (t.stop() * 1000); gpu_time[iter] += t_microseconds; } gpu_time[iter] /= n_sub_calls; } std::sort(gpu_time.begin(), gpu_time.end()); const int32_t mid = n_calls / 2; const double gpu_time_used = (n_calls % 2 == 0) ? (gpu_time[mid] + gpu_time[mid - 1]) / 2 : gpu_time[mid]; const rocsparse_format format = A.get_format(); switch(format) { case rocsparse_format_csc: case rocsparse_format_ell: case rocsparse_format_bell: case rocsparse_format_sell: case rocsparse_format_coo_aos: case rocsparse_format_coo: { break; } case rocsparse_format_csr: { auto& device = A.template as().device(); double gbyte_count = csrilu0_gbyte_count(device.m, device.nnz); const double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count); display_timing_info(display_key_t::M, device.m, display_key_t::nnz_A, device.nnz, display_key_t::bandwidth, gpu_gbyte, display_key_t::time_ms, get_gpu_time_msec(gpu_time_used)); break; } case rocsparse_format_bsr: { auto& device = A.template as().device(); double gbyte_count = bsrilu0_gbyte_count(device.mb, device.row_block_dim, device.nnzb); const double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count); display_timing_info(display_key_t::M, device.mb, display_key_t::nnzb, device.nnzb, display_key_t::bdim, device.row_block_dim, display_key_t::bandwidth, gpu_gbyte, display_key_t::time_ms, get_gpu_time_msec(gpu_time_used)); break; } } } } void testing_spilu0_extra(const Arguments& arg) {} #define INSTANTIATE(I, J, T) \ template void testing_spilu0_bad_arg(const Arguments& arg); \ template void testing_spilu0(const Arguments& arg) INSTANTIATE(int32_t, int32_t, float); INSTANTIATE(int32_t, int32_t, double); INSTANTIATE(int32_t, int32_t, rocsparse_float_complex); INSTANTIATE(int32_t, int32_t, rocsparse_double_complex); INSTANTIATE(int64_t, int32_t, float); INSTANTIATE(int64_t, int32_t, double); INSTANTIATE(int64_t, int32_t, rocsparse_float_complex); INSTANTIATE(int64_t, int32_t, rocsparse_double_complex); INSTANTIATE(int64_t, int64_t, float); INSTANTIATE(int64_t, int64_t, double); INSTANTIATE(int64_t, int64_t, rocsparse_float_complex); INSTANTIATE(int64_t, int64_t, rocsparse_double_complex); #undef INSTANTIATE