| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2022 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // * Redistributions of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // * 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. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // used to endorse or promote products derived from this software without |
| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS 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 COPYRIGHT OWNER 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 |
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| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Author: joydeepb@cs.utexas.edu (Joydeep Biswas) |
| |
| #ifndef CERES_INTERNAL_CUDA_KERNELS_H_ |
| #define CERES_INTERNAL_CUDA_KERNELS_H_ |
| |
| #include "ceres/internal/config.h" |
| |
| #ifndef CERES_NO_CUDA |
| |
| #include "cuda_runtime.h" |
| |
| namespace ceres { |
| namespace internal { |
| class Block; |
| class Cell; |
| |
| // Convert an array of double (FP64) values to float (FP32). Both arrays must |
| // already be on GPU memory. |
| void CudaFP64ToFP32(const double* input, |
| float* output, |
| const int size, |
| cudaStream_t stream); |
| |
| // Convert an array of float (FP32) values to double (FP64). Both arrays must |
| // already be on GPU memory. |
| void CudaFP32ToFP64(const float* input, |
| double* output, |
| const int size, |
| cudaStream_t stream); |
| |
| // Set all elements of the array to the FP32 value 0. The array must be in GPU |
| // memory. |
| void CudaSetZeroFP32(float* output, const int size, cudaStream_t stream); |
| |
| // Set all elements of the array to the FP64 value 0. The array must be in GPU |
| // memory. |
| void CudaSetZeroFP64(double* output, const int size, cudaStream_t stream); |
| |
| // Compute x = x + double(y). Input array is float (FP32), output array is |
| // double (FP64). Both arrays must already be on GPU memory. |
| void CudaDsxpy(double* x, float* y, const int size, cudaStream_t stream); |
| |
| // Compute y[i] = y[i] + d[i]^2 x[i]. All arrays must already be on GPU memory. |
| void CudaDtDxpy(double* y, |
| const double* D, |
| const double* x, |
| const int size, |
| cudaStream_t stream); |
| |
| // Compute structure of CRS matrix and permutation of values using block-sparse |
| // structure and temporary array row_block_ids. Array row_block_ids of size |
| // num_rows will be filled with indices of row-blocks corresponding to rows of |
| // CRS matrix. Arrays corresponding to CRS matrix, permutation and row_block_ids |
| // arrays are to be allocated by caller |
| void FillCRSStructure(const int num_row_blocks, |
| const int num_rows, |
| const int* row_block_offsets, |
| const Cell* cells, |
| const Block* row_blocks, |
| const Block* col_blocks, |
| int* rows, |
| int* cols, |
| int* row_block_ids, |
| int* permutation, |
| cudaStream_t stream); |
| |
| // Permute block of block-sparse values using permutation |
| // Pointer block_sparse_values corresponds to a block of num_values values from |
| // block-sparse matrix at the offset from begining. Pointer output corresponds |
| // to values of CRS matrix. Array permutation stores permutation from |
| // block-sparse to CRS matrix with permutation[i] being an index of i-th value |
| // of block-sparse matrix in values of CRS matrix |
| void PermuteValues(const int offset, |
| const int num_values, |
| const int* permutation, |
| const double* block_sparse_values, |
| double* crs_values, |
| cudaStream_t stream); |
| |
| } // namespace internal |
| } // namespace ceres |
| |
| #endif // CERES_NO_CUDA |
| |
| #endif // CERES_INTERNAL_CUDA_KERNELS_H_ |