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grid_gradient_GPU.cuh
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R1448 Lenstool-HPC
grid_gradient_GPU.cuh
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/**
Lenstool-HPC: HPC based massmodeling software and Lens-map generation
Copyright (C) 2017 Christoph Schaefer, EPFL (christophernstrerne.schaefer@epfl.ch), Gilles Fourestey (gilles.fourestey@epfl.ch)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
@brief: Function for first order derivative computation over a grid
*/
#ifndef GRID_GRADIENT_GPU_CUH_
#define GRID_GRADIENT_GPU_CUH_
//#include "cudafunctions.cuh"
//#include "gradient_GPU.cuh"
#include <structure_hpc.hpp>
//gradient_grid_GPU_sorted(double*, double*, grid_param const*, Potential_SOA const*, int, int)
//static
//extern "C"
void gradient_grid_GPU_sorted(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int Nlens, int nbgridcells);
void gradient_grid_GPU(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int Nlens, int nbgridcells);
//
void gradient_grid_GPU(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int nhalos, type_t dx, type_t dy, int nbgridcells_x, int nbgridcells_y, int istart = 0, int jstart = 0);
//
void gradient_grid_GPU_UM(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int nhalos, type_t dx, type_t dy, int nbgridcells_x, int nbgridcells_y, int istart, int jstart);
//
void module_potentialDerivatives_totalGradient_SOA_CPU_GPU(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens_gpu, int nbgridcells, int nhalos);
void module_potentialDerivatives_totalGradient_SOA_CPU_GPU(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int nhalos, type_t dx, type_t dy, int nbgridcells_x, int nbgridcells_y, int istart, int jstart);
//
#if 0
//
//void
//gradient_grid_GPU_sorted(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int Nlens, int nbgridcells);
void
module_potentialDerivatives_totalGradient_SOA_CPU_GPU(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens_cpu, const struct Potential_SOA *lens_gpu, int nbgridcells, int nhalos);
//
void
gradient_grid_pinned(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int *Nlens,int nbgridcell);
void
gradient_grid_pinned_multiple(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int *Nlens,int nbgridcell);
void
gradient_grid_GPU_sub(type_t *grid_grad_x, type_t *grid_grad_y, const struct grid_param *frame, const struct Potential_SOA *lens, int nhalos,int nbgridcells, int indexactual, int Ncells );
#endif
#endif /* GRADIENTGPU_CUH_ */
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