// Copyright (c) 2020-2025 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 #include #include #include #include #include #include #include #include #include "include/host_device.h" // This example computes a summed area table using segmented scan // http://en.wikipedia.org/wiki/Summed_area_table // convert a linear index to a linear index in the transpose struct transpose_index { size_t m, n; __host__ __device__ transpose_index(size_t _m, size_t _n) : m(_m) , n(_n) {} __host__ __device__ size_t operator()(size_t linear_index) { size_t i = linear_index / n; size_t j = linear_index % n; return m * j + i; } }; // convert a linear index to a row index struct row_index { size_t n; __host__ __device__ row_index(size_t _n) : n(_n) {} __host__ __device__ size_t operator()(size_t i) { return i / n; } }; // transpose an M-by-N array template void transpose(size_t m, size_t n, thrust::device_vector& src, thrust::device_vector& dst) { thrust::counting_iterator indices(0); thrust::gather(thrust::make_transform_iterator(indices, transpose_index(n, m)), thrust::make_transform_iterator(indices, transpose_index(n, m)) + dst.size(), src.begin(), dst.begin()); } // scan the rows of an M-by-N array template void scan_horizontally(size_t n, thrust::device_vector& d_data) { thrust::counting_iterator indices(0); thrust::inclusive_scan_by_key( thrust::make_transform_iterator(indices, row_index(n)), thrust::make_transform_iterator(indices, row_index(n)) + d_data.size(), d_data.begin(), d_data.begin()); } // print an M-by-N array template void print(size_t m, size_t n, thrust::device_vector& d_data) { thrust::host_vector h_data = d_data; for (size_t i = 0; i < m; i++) { for (size_t j = 0; j < n; j++) { std::cout << std::setw(8) << h_data[i * n + j] << " "; } std::cout << "\n"; } } int main(void) { size_t m = 3; // number of rows size_t n = 4; // number of columns // 2d array stored in row-major order [(0,0), (0,1), (0,2) ... ] thrust::device_vector data(m * n, 1); std::cout << "[step 0] initial array" << std::endl; print(m, n, data); std::cout << "[step 1] scan horizontally" << std::endl; scan_horizontally(n, data); print(m, n, data); std::cout << "[step 2] transpose array" << std::endl; thrust::device_vector temp(m * n); transpose(m, n, data, temp); print(n, m, temp); std::cout << "[step 3] scan transpose horizontally" << std::endl; scan_horizontally(m, temp); print(n, m, temp); std::cout << "[step 4] transpose the transpose" << std::endl; transpose(n, m, temp, data); print(m, n, data); return 0; }