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339 lines
16 KiB
C++
339 lines
16 KiB
C++
/* ************************************************************************
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* Copyright (C) 2020 Advanced Micro Devices, Inc. All rights Reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*
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* ************************************************************************ */
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#pragma once
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#ifndef TESTING_DENSE2CSX_HPP
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#define TESTING_DENSE2CSX_HPP
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#include "flops.hpp"
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#include "gbyte.hpp"
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#include "hipsparse.hpp"
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#include "hipsparse_arguments.hpp"
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#include "hipsparse_test_unique_ptr.hpp"
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#include "unit.hpp"
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#include "utility.hpp"
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#include <algorithm>
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#include <hipsparse.h>
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#include <string>
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using namespace hipsparse;
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using namespace hipsparse_test;
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#include <iostream>
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template <hipsparseDirection_t DIRA, typename T, typename FUNC>
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void testing_dense2csx_bad_arg(FUNC& dense2csx)
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{
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#if(!defined(CUDART_VERSION))
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static constexpr int M = 1;
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static constexpr int N = 1;
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static constexpr int LD = M;
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std::unique_ptr<handle_struct> unique_ptr_handle(new handle_struct);
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hipsparseHandle_t handle = unique_ptr_handle->handle;
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std::unique_ptr<descr_struct> unique_ptr_descr(new descr_struct);
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hipsparseMatDescr_t descr = unique_ptr_descr->descr;
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auto m_csx_val = hipsparse_unique_ptr{device_malloc(sizeof(T) * 1), device_free};
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auto m_dense_val = hipsparse_unique_ptr{device_malloc(sizeof(T) * 1), device_free};
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auto m_nnzPerRowColumn = hipsparse_unique_ptr{device_malloc(sizeof(int) * 1), device_free};
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auto m_csx_row_col_ptr
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= hipsparse_unique_ptr{device_malloc(sizeof(int) * (1 + 1)), device_free};
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auto m_csx_row_col_ind = hipsparse_unique_ptr{device_malloc(sizeof(int) * 1), device_free};
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T* d_dense_val = (T*)m_dense_val.get();
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T* d_csx_val = (T*)m_csx_val.get();
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int* d_nnzPerRowColumn = (int*)m_nnzPerRowColumn.get();
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int* d_csx_row_col_ptr = (int*)m_csx_row_col_ptr.get();
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int* d_csx_col_row_ind = (int*)m_csx_row_col_ind.get();
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int local_ptr[2] = {0, 1};
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CHECK_HIP_ERROR(
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hipMemcpy(d_csx_row_col_ptr, local_ptr, sizeof(int) * (1 + 1), hipMemcpyHostToDevice));
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verify_hipsparse_status_invalid_handle(dense2csx(
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nullptr, 0, 0, nullptr, (const T*)nullptr, 0, nullptr, (T*)nullptr, nullptr, nullptr));
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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nullptr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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descr,
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nullptr,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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nullptr,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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nullptr,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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nullptr,
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d_csx_col_row_ind),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_pointer(dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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nullptr),
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"Error: an invalid pointer must be detected.");
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verify_hipsparse_status_invalid_size(dense2csx(handle,
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-1,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: An invalid size must be detected.");
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verify_hipsparse_status_invalid_size(dense2csx(handle,
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M,
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-1,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: An invalid size must be detected.");
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verify_hipsparse_status_invalid_size(dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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M - 1,
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d_nnzPerRowColumn,
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d_csx_val,
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d_csx_row_col_ptr,
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d_csx_col_row_ind),
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"Error: An invalid size must be detected.");
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#endif
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}
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template <hipsparseDirection_t DIRA, typename T, typename FUNC>
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void testing_dense2csx(const Arguments& argus, FUNC& dense2csx)
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{
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int M = argus.M;
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int N = argus.N;
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int LD = argus.lda;
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hipsparseIndexBase_t idx_base = argus.baseA;
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std::unique_ptr<handle_struct> unique_ptr_handle(new handle_struct);
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hipsparseHandle_t handle = unique_ptr_handle->handle;
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std::unique_ptr<descr_struct> unique_ptr_descr(new descr_struct);
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hipsparseMatDescr_t descr = unique_ptr_descr->descr;
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CHECK_HIPSPARSE_ERROR(hipsparseSetMatIndexBase(descr, idx_base));
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int DIMDIR = (HIPSPARSE_DIRECTION_ROW == DIRA) ? M : N;
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std::vector<T> h_dense_val(LD * N);
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std::vector<int> h_nnzPerRowColumn(DIMDIR);
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// Create the dense matrix.
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auto m_dense_val = hipsparse_unique_ptr{device_malloc(sizeof(T) * LD * N), device_free};
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auto nnzPerRowColumn_managed
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= hipsparse_unique_ptr{device_malloc(sizeof(int) * DIMDIR), device_free};
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auto nnzTotalDevHostPtr_managed
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= hipsparse_unique_ptr{device_malloc(sizeof(int) * 1), device_free};
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T* d_dense_val = (T*)m_dense_val.get();
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int* d_nnzPerRowColumn = (int*)nnzPerRowColumn_managed.get();
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// Initialize the entire allocated memory.
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for(int i = 0; i < LD; ++i)
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{
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for(int j = 0; j < N; ++j)
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{
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h_dense_val[j * LD + i] = make_DataType<T>(-1);
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}
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}
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// Initialize a random dense matrix.
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srand(0);
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gen_dense_random_sparsity_pattern(M, N, h_dense_val.data(), LD, HIPSPARSE_ORDER_COL, 0.2);
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// Transfer.
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CHECK_HIP_ERROR(
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hipMemcpy(d_dense_val, h_dense_val.data(), sizeof(T) * LD * N, hipMemcpyHostToDevice));
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int nnz;
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CHECK_HIPSPARSE_ERROR(hipsparseSetPointerMode(handle, HIPSPARSE_POINTER_MODE_HOST));
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CHECK_HIPSPARSE_ERROR(
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hipsparseXnnz(handle, DIRA, M, N, descr, d_dense_val, LD, d_nnzPerRowColumn, &nnz));
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// Transfer.
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CHECK_HIP_ERROR(hipMemcpy(
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h_nnzPerRowColumn.data(), d_nnzPerRowColumn, sizeof(int) * DIMDIR, hipMemcpyDeviceToHost));
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auto m_csx_row_col_ptr
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= hipsparse_unique_ptr{device_malloc(sizeof(int) * (DIMDIR + 1)), device_free};
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auto m_csx_val = hipsparse_unique_ptr{device_malloc(sizeof(T) * nnz), device_free};
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auto m_csx_col_row_ind = hipsparse_unique_ptr{device_malloc(sizeof(int) * nnz), device_free};
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int* d_csx_row_col_ptr = (int*)m_csx_row_col_ptr.get();
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int* d_csx_col_row_ind = (int*)m_csx_col_row_ind.get();
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T* d_csx_val = (T*)m_csx_val.get();
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std::vector<int> cpu_csx_row_col_ptr(DIMDIR + 1);
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std::vector<T> cpu_csx_val(nnz);
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std::vector<int> cpu_csx_col_row_ind(nnz);
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if(argus.unit_check)
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{
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// Compute the reference host first.
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host_dense2csx<DIRA, T>(M,
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N,
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hipsparseGetMatIndexBase(descr),
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h_dense_val.data(),
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LD,
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h_nnzPerRowColumn.data(),
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cpu_csx_val.data(),
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cpu_csx_row_col_ptr.data(),
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cpu_csx_col_row_ind.data());
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CHECK_HIPSPARSE_ERROR(
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dense2csx(handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_row_col_ptr : d_csx_col_row_ind,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_col_row_ind : d_csx_row_col_ptr));
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void* buffer = malloc(std::max(sizeof(T), sizeof(int)) * std::max(DIMDIR + 1, nnz));
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// Transfer and check results.
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CHECK_HIP_ERROR(hipMemcpy(buffer, d_csx_val, sizeof(T) * nnz, hipMemcpyDeviceToHost));
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unit_check_general(1, nnz, 1, cpu_csx_val.data(), (T*)buffer);
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CHECK_HIP_ERROR(
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hipMemcpy(buffer, d_csx_col_row_ind, sizeof(int) * nnz, hipMemcpyDeviceToHost));
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unit_check_general(1, nnz, 1, cpu_csx_col_row_ind.data(), (int*)buffer);
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CHECK_HIP_ERROR(hipMemcpy(
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buffer, d_csx_row_col_ptr, sizeof(int) * (DIMDIR + 1), hipMemcpyDeviceToHost));
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unit_check_general(1, (DIMDIR + 1), 1, cpu_csx_row_col_ptr.data(), (int*)buffer);
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free(buffer);
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buffer = nullptr;
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}
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if(argus.timing)
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{
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int number_cold_calls = 2;
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int number_hot_calls = argus.iters;
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// Warm-up
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for(int iter = 0; iter < number_cold_calls; ++iter)
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{
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CHECK_HIPSPARSE_ERROR(dense2csx(
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handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_row_col_ptr : d_csx_col_row_ind,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_col_row_ind : d_csx_row_col_ptr));
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}
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double gpu_time_used = get_time_us();
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// Performance run
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for(int iter = 0; iter < number_hot_calls; ++iter)
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{
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CHECK_HIPSPARSE_ERROR(dense2csx(
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handle,
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M,
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N,
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descr,
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d_dense_val,
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LD,
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d_nnzPerRowColumn,
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d_csx_val,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_row_col_ptr : d_csx_col_row_ind,
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(DIRA == HIPSPARSE_DIRECTION_ROW) ? d_csx_col_row_ind : d_csx_row_col_ptr));
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}
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gpu_time_used = (get_time_us() - gpu_time_used) / number_hot_calls;
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double gbyte_count = dense2csx_gbyte_count<DIRA, T>(M, N, nnz);
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double gpu_gbyte = get_gpu_gbyte(gpu_time_used, gbyte_count);
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std::cout << "GBytes/s: " << gpu_gbyte << " time (ms): " << get_gpu_time_msec(gpu_time_used)
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<< std::endl;
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}
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}
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#endif // TESTING_DENSE2CSX_HPP
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