/* ************************************************************************** * Copyright (C) 2025-2026 Advanced Micro Devices, Inc. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * SUCH DAMAGE. * *************************************************************************/ #pragma once #include "common/misc/client_util.hpp" #include "common/misc/clientcommon.hpp" #include "common/misc/lapack_host_reference.hpp" #include "common/misc/norm.hpp" #include "common/misc/rocsolver.hpp" #include "common/misc/rocsolver_arguments.hpp" #include "common/misc/rocsolver_test.hpp" #include "common/misc/rocsolver_timer.hpp" template void lange_checkBadArgs(const rocblas_handle handle, const rocsolver_norm_type norm_type, const I m, const I n, T dA, const I lda, S dnorms) { // handle EXPECT_ROCBLAS_STATUS(rocsolver_lange(nullptr, norm_type, m, n, dA, lda, dnorms), rocblas_status_invalid_handle); // values EXPECT_ROCBLAS_STATUS( rocsolver_lange(handle, static_cast(0), m, n, dA, lda, dnorms), rocblas_status_invalid_value); // pointers EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, n, (T) nullptr, lda, dnorms), rocblas_status_invalid_pointer); EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, n, dA, lda, (S) nullptr), rocblas_status_invalid_pointer); // quick return with invalid pointers EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, (I)0, n, (T) nullptr, lda, (S) nullptr), rocblas_status_success); EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, (I)0, (T) nullptr, lda, (S) nullptr), rocblas_status_success); } template void testing_lange_bad_arg() { using S = decltype(std::real(T{})); // safe arguments rocblas_local_handle handle; rocsolver_norm_type norm_type = rocsolver_norm_type_max; I m = 1; I n = 1; I lda = 1; // memory allocation device_strided_batch_vector dA(1, 1, 1, 1); device_strided_batch_vector dnorms(1, 1, 1, 1); CHECK_HIP_ERROR(dA.memcheck()); CHECK_HIP_ERROR(dnorms.memcheck()); // check bad arguments lange_checkBadArgs(handle, norm_type, m, n, dA.data(), lda, dnorms.data()); } template void lange_initData(const rocblas_handle handle, const rocsolver_norm_type norm_type, const I m, const I n, Td& dA, const I lda, Sd& dnorms, Th& hA, Sh& hnorms) { if(CPU) { rocblas_init(hA, true); } if(GPU) { // copy data from CPU to device CHECK_HIP_ERROR(dA.transfer_from(hA)); } } template void lange_getError(const rocblas_handle handle, const rocsolver_norm_type norm_type, const I m, const I n, Td& dA, const I lda, Sd& dnorms, Th& hA, Sh& hnorms, Sh& hnorms_res, double* max_err) { // Workspace for CPU lange (max needed is for 1-norm or infinity-norm) size_t size_work = std::max(m, n); std::vector work(size_work); // initialize data lange_initData(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms); // execute computations // GPU lapack CHECK_ROCBLAS_ERROR(rocsolver_lange(handle, norm_type, m, n, dA.data(), lda, dnorms.data())); CHECK_HIP_ERROR(hnorms_res.transfer_from(dnorms)); // CPU lapack char norm = rocsolver2char_norm_type(norm_type); hnorms[0][0] = cpu_lange(norm, m, n, hA[0], lda, work.data()); // error is ||hnorms - hnorms_res|| / ||hnorms|| // using absolute value since we only have a single scalar *max_err = std::abs(hnorms[0][0] - hnorms_res[0][0]) / std::abs(hnorms[0][0]); } template void lange_getPerfData(const rocblas_handle handle, const rocsolver_norm_type norm_type, const I m, const I n, Td& dA, const I lda, Sd& dnorms, Th& hA, Sh& hnorms, double* gpu_time_used, double* cpu_time_used, const rocblas_int hot_calls, const int profile, const bool profile_kernels, const bool perf) { // Workspace for CPU lange size_t size_work = std::max(m, n); std::vector work(size_work); // only init CPU data once as it is not overwritten lange_initData(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms); if(!perf) { // cpu-lapack performance (only if not in perf mode) char norm = rocsolver2char_norm_type(norm_type); *cpu_time_used = get_time_us_no_sync(); hnorms[0][0] = cpu_lange(norm, m, n, hA[0], lda, work.data()); *cpu_time_used = get_time_us_no_sync() - *cpu_time_used; } // cold calls for(int iter = 0; iter < 2; iter++) { lange_initData(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms); CHECK_ROCBLAS_ERROR(rocsolver_lange(handle, norm_type, m, n, dA.data(), lda, dnorms.data())); } // gpu-lapack performance hipStream_t stream; CHECK_ROCBLAS_ERROR(rocblas_get_stream(handle, &stream)); rocsolver_timer timer; if(profile > 0) { if(profile_kernels) rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile | rocblas_layer_mode_ex_log_kernel); else rocsolver_log_set_layer_mode(rocblas_layer_mode_log_profile); rocsolver_log_set_max_levels(profile); } for(int iter = 0; iter < hot_calls; iter++) { lange_initData(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms); timer.start(stream); rocsolver_lange(handle, norm_type, m, n, dA.data(), lda, dnorms.data()); timer.end(stream); } *gpu_time_used = timer.get_combined(); } template void testing_lange(Arguments& argus) { using S = real_t; // get arguments rocblas_local_handle handle; char norm_typeC = argus.get("norm_type"); I m = argus.get("m"); I n = argus.get("n", m); I lda = argus.get("lda", m); rocsolver_norm_type norm_type = char2rocsolver_norm_type(norm_typeC); rocblas_int hot_calls = argus.iters; // check non-supported values if(norm_type != rocsolver_norm_type_one && norm_type != rocsolver_norm_type_frobenius && norm_type != rocsolver_norm_type_infinity && norm_type != rocsolver_norm_type_max) { EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, n, (T*)nullptr, lda, (S*)nullptr), rocblas_status_invalid_value); if(argus.timing) rocsolver_bench_inform(inform_invalid_args); return; } // determine sizes size_t size_A = size_t(lda) * n; size_t size_norms = 1; double max_error = 0, gpu_time_used = 0, cpu_time_used = 0; size_t size_norms_res = (argus.unit_check || argus.norm_check) ? size_norms : 0; // check invalid sizes bool invalid_size = (m < 0 || n < 0 || lda < m); if(invalid_size) { EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, n, (T*)nullptr, lda, (S*)nullptr), rocblas_status_invalid_size); if(argus.timing) rocsolver_bench_inform(inform_invalid_size); return; } // memory size query is necessary if(argus.mem_query) { CHECK_ROCBLAS_ERROR(rocblas_start_device_memory_size_query(handle)); CHECK_ALLOC_QUERY(rocsolver_lange(handle, norm_type, m, n, (T*)nullptr, lda, (S*)nullptr)); size_t size; CHECK_ROCBLAS_ERROR(rocblas_stop_device_memory_size_query(handle, &size)); rocsolver_bench_inform(inform_mem_query, size); return; } // memory allocations host_strided_batch_vector hA(size_A, 1, size_A, 1); host_strided_batch_vector hnorms(size_norms, 1, size_norms, 1); host_strided_batch_vector hnorms_res(size_norms_res, 1, size_norms_res, 1); device_strided_batch_vector dA(size_A, 1, size_A, 1); device_strided_batch_vector dnorms(size_norms, 1, size_norms, 1); if(size_A) CHECK_HIP_ERROR(dA.memcheck()); CHECK_HIP_ERROR(dnorms.memcheck()); // check quick return if(n == 0 || m == 0) { EXPECT_ROCBLAS_STATUS(rocsolver_lange(handle, norm_type, m, n, dA.data(), lda, dnorms.data()), rocblas_status_success); if(argus.timing) rocsolver_bench_inform(inform_quick_return); return; } // check computations if(argus.unit_check || argus.norm_check) lange_getError(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms, hnorms_res, &max_error); // collect performance data if(argus.timing && hot_calls > 0) { lange_getPerfData(handle, norm_type, m, n, dA, lda, dnorms, hA, hnorms, &gpu_time_used, &cpu_time_used, hot_calls, argus.profile, argus.profile_kernels, argus.perf); } // validate results for rocsolver-test if(argus.unit_check) { if(norm_type == rocsolver_norm_type_one) { ROCSOLVER_TEST_CHECK(T, max_error, m); // column sums of m elements } else if(norm_type == rocsolver_norm_type_infinity) { ROCSOLVER_TEST_CHECK(T, max_error, n); // row sums of n elements } else if(norm_type == rocsolver_norm_type_max) { ROCSOLVER_TEST_CHECK(T, max_error, 1); // no summation } else { ROCSOLVER_TEST_CHECK(T, max_error, m * n); // Frobenius: sum of m*n terms } } // output results for rocsolver-bench if(argus.timing) { if(!argus.perf) { rocsolver_bench_header("Arguments:"); rocsolver_bench_output("norm_type", "m", "n", "lda"); rocsolver_bench_output(norm_typeC, m, n, lda); rocsolver_bench_header("Results:"); if(argus.norm_check) { rocsolver_bench_output("cpu_time_us", "gpu_time_us", "error"); rocsolver_bench_output(cpu_time_used, gpu_time_used, max_error); } else { rocsolver_bench_output("cpu_time_us", "gpu_time_us"); rocsolver_bench_output(cpu_time_used, gpu_time_used); } rocsolver_bench_endl(); } else { if(argus.norm_check) rocsolver_bench_output(gpu_time_used, max_error); else rocsolver_bench_output(gpu_time_used); } } // ensure all arguments were consumed argus.validate_consumed(); } #define EXTERN_TESTING_LANGE(...) extern template void testing_lange<__VA_ARGS__>(Arguments&); INSTANTIATE(EXTERN_TESTING_LANGE, FOREACH_SCALAR_TYPE, FOREACH_INT_TYPE, APPLY_STAMP)