internal/ceres/cuda_kernels.h

// 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
// 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.
//
// 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_