204 lines
8.1 KiB
C++
204 lines
8.1 KiB
C++
/*
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<moCudakernelEval.h>
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Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
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Karima Boufaras, Thé Van LUONG
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This software is governed by the CeCILL license under French law and
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abiding by the rules of distribution of free software. You can use,
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modify and/ or redistribute the software under the terms of the CeCILL
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license as circulated by CEA, CNRS and INRIA at the following URL
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"http://www.cecill.info".
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As a counterpart to the access to the source code and rights to copy,
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modify and redistribute granted by the license, users are provided only
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with a limited warranty and the software's author, the holder of the
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economic rights, and the successive licensors have only limited liability.
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In this respect, the user's attention is drawn to the risks associated
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with loading, using, modifying and/or developing or reproducing the
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software by the user in light of its specific status of free software,
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that may mean that it is complicated to manipulate, and that also
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therefore means that it is reserved for developers and experienced
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professionals having in-depth computer knowledge. Users are therefore
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encouraged to load and test the software's suitability as regards their
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requirements in conditions enabling the security of their systems and/or
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data to be ensured and, more generally, to use and operate it in the
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same conditions as regards security.
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The fact that you are presently reading this means that you have had
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knowledge of the CeCILL license and that you accept its terms.
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ParadisEO WebSite : http://paradiseo.gforge.inria.fr
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Contact: paradiseo-help@lists.gforge.inria.fr
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*/
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#ifndef __moCudakernelEval_H
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#define __moCudakernelEval_H
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/**
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* The kernel function called from the host and executed in device to compute all neighbors fitness at one time
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* @param _eval how to evaluate each neighbor
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* @param _solution representation of solution( vector of int,float....)
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* @param _allFitness Array of Fitness to save all neighbors fitness
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* @param _fitness the current solution fitness
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* @param _neighborhoodsize the size of the neighborhood
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*/
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template<class EOT, class Fitness, class Neighbor, class IncrementEval>
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__global__ void kernelEval(IncrementEval _eval, EOT _solution, Fitness* _allFitness,
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Fitness _fitness, unsigned _neighborhoodsize) {
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// The thread identifier within a grid block's
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int id = blockIdx.x * blockDim.x + threadIdx.x;
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// array to save index to be changed
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unsigned int index[1];
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// In this representation each id identify one and only one neighbor in neighborhood
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if (id < _neighborhoodsize) {
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//Change the id'th element of solution
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index[0]=id;
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//Compute fitness for id'th neighbor
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_allFitness[id] = _eval(_solution, _fitness,index);
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/**
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* The kernel function called from the host and executed in device to compute all flip neighbors fitness at one time
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* @param _eval how to evaluate each neighbor
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* @param _solution representation of solution to flip
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* @param _allFitness Array of Fitness type to save all neighbors fitness
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* @param _fitness the current solution fitness
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* @param _neighborhoodsize the size of the neighborhood
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* @param _mapping the neighborhood mapping
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* @param _Kflip the number of bit to flip
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*/
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template<class EOT, class Fitness, class Neighbor, class IncrementEval>
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__global__ void kernelKflip(IncrementEval _eval, EOT _solution, Fitness* _allFitness,
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Fitness _fitness, unsigned _neighborhoodsize, unsigned * _mapping,unsigned _Kflip) {
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// The thread identifier within a grid block's
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int id = blockIdx.x * blockDim.x + threadIdx.x;
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//save temporary fitness
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unsigned tmp_fitness;
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//counter of number of flip to do
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unsigned i;
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// array to save index to be changed
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unsigned index[1];
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// In this representation each id identify one and only one neighbor in neighborhood
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if (id < _neighborhoodsize) {
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//Init fitness with fitness of solution
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tmp_fitness=_fitness;
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//Evaluate neighbor after Kflip
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for(i=0;i<=_Kflip;i++){
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//The designed index to flip
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index[0]=_mapping[id + i * _neighborhoodsize];
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//Evaluate the neighbor
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tmp_fitness= _eval(_solution, tmp_fitness, index);
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}
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//The final fitness of the Id'th neighbor
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_allFitness[id]=tmp_fitness;
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/**
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* The kernel function called from the host and executed in device to compute all swap neighbors fitness at one time
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* @param _eval how to evaluate each neighbor
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* @param _solution representation ofsolution to swap
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* @param _sol_tmp to save temporary a solution element to swap
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* @param _allFitness Array of Fitness type to save all neighbors fitness
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* @param _fitness the current solution fitness
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* @param _neighborhoodsize the size of the neighborhood
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* @param _mapping the neighborhood mapping
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* @param _Kswap the number of swap to do
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* @param _size the solution size
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*/
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template<class EOT,class Fitness, class Neighbor, class IncrementEval>
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__global__ void kernelKswap(IncrementEval _eval,EOT _solution ,EOT _sol_tmp, Fitness* _allFitness,
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Fitness _fitness, unsigned _neighborhoodsize, unsigned * _mapping,unsigned _Kswap,unsigned _size) {
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// The thread identifier within a grid block's
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int id = blockIdx.x * blockDim.x + threadIdx.x;
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//save temporary fitness
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int tmp_fitness;
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//counter of number of swap to do
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unsigned i;
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// array to save index to be changed, solution size & thread id
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unsigned index[4];
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// In this representation each id identify one and only one neighbor in neighborhood
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if (id < _neighborhoodsize) {
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//the first index to swap
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index[0]=_mapping[id];
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//the second index to swap
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index[1]=_mapping[id +_neighborhoodsize];
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//the solution size
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index[2]=_size;
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//the thread id
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index[3]=id;
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//Init the temporary fitness with the initial solution fitness
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tmp_fitness=_fitness;
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//Evaluate neighbor after K-swap
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for(i=2;i<=_Kswap+1;i++){
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//Evaluate neighbor with index case
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tmp_fitness=_eval(_solution, tmp_fitness, index);
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//Permut the solution
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_sol_tmp[id]=_solution[index[0]+id*index[2]];
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_solution[index[0]+id*index[2]]=_solution[index[1]+id*index[2]];
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_solution[index[1]+id*index[2]]=_sol_tmp[id];
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//Init the next swap to do
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index[0]=index[1];
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index[1]=_mapping[id +i*_neighborhoodsize];
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}
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//save the final fitness of the id'th neighbor
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_allFitness[id]=tmp_fitness;
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/**
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* The kernel function called from the host and executed in device to compute all permutation neighbors fitness at one time
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* @param _eval how to evaluate each neighbor
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* @param _solution representation of solution
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* @param _allFitness Array of Fitness type to save all neighbors fitness
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* @param _fitness the current solution fitness
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* @param _neighborhoodsize the size of the neighborhood
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* @param _mapping the neighborhood mapping
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* @param _size the solution size
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*/
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template<class EOT, class Fitness, class Neighbor, class IncrementEval>
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__global__ void kernelPermutation(IncrementEval _eval, EOT _solution, Fitness* _allFitness,
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Fitness _fitness, unsigned _neighborhoodsize, unsigned * _mapping,unsigned _size) {
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// The thread identifier within a grid block's
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int id = blockIdx.x * blockDim.x + threadIdx.x;
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// array to save index to be changed, solution size
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unsigned index[4];
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// In this representation each id identify one and only one neighbor in neighborhood
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if (id < _neighborhoodsize) {
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//The first index of permutation
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index[0]=_mapping[id];
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//The second index of permutation
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index[1]=_mapping[id +_neighborhoodsize];
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//The solution size
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index[2]=_size;
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//Puch 0 in the 3 index
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index[3]=0;
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_allFitness[id]=_eval(_solution,_fitness,index);
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}
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}
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#endif
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