Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F94920090
grid_gradient_GPU.cuh
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Wed, Dec 11, 10:04
Size
3 KB
Mime Type
text/x-c
Expires
Fri, Dec 13, 10:04 (1 d, 21 h)
Engine
blob
Format
Raw Data
Handle
22900030
Attached To
R1448 Lenstool-HPC
grid_gradient_GPU.cuh
View Options
/**
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_ */
Event Timeline
Log In to Comment