Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

Genetic Programming and Evolvable Machines

Volumn 10, Issue 4, 2009, Pages 391-415

  Munawar, Asim ^a   Wahib, Mohamed ^a   Munetomo, Masaharu ^a   Akama, Kiyoshi ^a  

^a HOKKAIDO UNIVERSITY   (Japan)

Author keywords

Compute unified device architecture (CUDA); General purpose computing on graphics processing unit (GPGPU); Genetic algorithm (GA); MAXimum SATisfiability problem (MAX SAT); Single instruction multiple data (SIMD)

Indexed keywords

ALGORITHMIC DESIGN; COMPUTE UNIFIED DEVICE ARCHITECTURE (CUDA); COMPUTE UNIFIED DEVICE ARCHITECTURES; EFFICIENT IMPLEMENTATION; GENERAL-PURPOSE COMPUTING; GENERAL-PURPOSE COMPUTING ON GRAPHICS PROCESSING UNIT (GPGPU); GENETIC OPERATORS; GRAPHICAL PROCESSING UNITS; GRAPHICS HARDWARE; LITTLE RESEARCH; LOCAL SEARCH; LS ALGORITHM; MAX-SAT; MAX-SAT PROBLEMS; MAXIMUM SATISFIABILITY; MAXIMUM SATISFIABILITY PROBLEM (MAX-SAT); META HEURISTICS; MULTIPLE THREADS; NUMERICAL TESTS; OPTIMIZATION TECHNIQUES; OVERALL EXECUTION; PARALLEL COMPUTING; PARALLELIZING; PERFORMANCE MEASUREMENTS; PRACTICAL IMPORTANCE; SEARCH METHOD; SINGLE INSTRUCTION MULTIPLE DATA (SIMD); SOFTWARE DEVELOPMENT;

COMPUTER GRAPHICS EQUIPMENT; COMPUTER SCIENCE; GASES; IMAGE CODING; MATHEMATICAL OPERATORS; PARALLEL ARCHITECTURES; PROGRAM PROCESSORS; SOFTWARE DESIGN;

GENETIC ALGORITHMS;

EID: 70449517340     PISSN: 13892576     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10710-009-9091-4     Document Type: Article

References (24)

1. http://www.nvidia.com/cuda/
2. http://www.openmp.org/
3. nVidia CUDA Programming Guide 2.1 - CUDA 2.1 SDK Documentation (2008). http://www.nvidia.com/cuda/
4. E. Alba, B. Dorronsoro, Cellular Genetic Algorithms, Operations Research/Computer Science Interfaces Series, vol. 42 (Springer, 2008)
5. D. Boughaci, H. Drias, Solving weighted max-sat optimization problems using a taboo scatter search metaheuristic. in SAC '04: Proceedings of the 2004 ACM Symposium on Applied Computing (ACM, New York, 2004), pp. 35-36
6. D. Boughaci, H. Drias, B. Benhamou, Solving max-sat problems using a memetic evolutionary meta-heuristic, in Cybernetics and Intelligent Systems, 2004 IEEE Conference on Publication, vol. 1. (2004), pp. 480-484
7. H. Drias, Scatter search with walk strategy for solving hard max-w-sat problems, in Proceedings of IEA- AIE2001m Lecture Notes in Computer Science, LNAI-2070 (Springer, Budapest, 2001), p. 3544
8. K. Fok T. Wong M. Wong 2007 Evolutionary computing on consumer graphics hardware IEEE Int. Syst. 22 2 69 78 10.1109/MIS.2007.28 (Pubitemid 46495748)
9. J. Frank, A study of genetic algorithms to find approximate solutions to hard 3cnf problems, in Golden West International Conference on Artificial Intelligence (Kluwer Academic Publishers, 1994)
10. H. Hoos, T. Stutzle, Satlib: An Online Resource for Research on Sat (IOS Press, 2000), pp. 283-292. SATLIB is available online at http://www.satlib.org
11. S. Kirkpatrick, C. Gelatt, M. Vecchi, Optimization by simulated annealing. Science, Number 4598, 13 May 1983 220, 4598, 671-680 (1983)
12. C. Li, Exploiting yet more the power of unit clause propagation to solve 3-sat problem, in ECAI'96 Workshop on Advances in Propositional Deduction (Budapest, Hungary, 1996), pp. 11-16
13. C. Li, Anbulagan: Heuristics based on unit propagation for satisfiability problems, in IJCAI (1), (1997), pp. 366-371
14. J. Li, X. Wang, R. He, Z. Chi, An efficient fine-grained parallel genetic algorithm based on gpu-accelerated, in NPC '07: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (IEEE Computer Society, Washington, DC, 2007), pp. 855-862
15. E. Lindholm J. Nickolls S. Oberman J. Montrym 2008 Nvidia tesla: a unified graphics and computing architecture Micro. IEEE 28 2 39 55 10.1109/MM.2008.31 (Pubitemid 351796170)
16. D. Martin L. George L. Donald 1962 A machine program for theorem-proving Commun. ACM 5 7 394 397 10.1145/368273.368557
17. M. Matsumoto T. Nishimura 1998 Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator ACM Trans. Model. Comput. Simul. 8 1 3 30 0917.65005 10.1145/272991.272995
18. M. Matsumoto, T. Nishimura, Dynamic creation of pseudorandom number generators, in Monte Carlo and Quasi-Monte Carlo Methods 1998 (Springer, 2000), pp. 56-69
19. B. Mazure, L. Sais, E. Crmoire, A tabu search for sat, in Proceedings of AAAI (1997)
20. V. Podlozhnyuk, Parallel mersenne twister. CUDA 2.1 SDK Documentation (2007)
21. B. Selman, H. Kautz, B. Cohen, Noise strategies for improving local search (1994)
22. J. Stratton, S. Stone, W. Hwu, Mcuda: an efficient implementation of cuda kernels on multi-cores. Technical Report IMPACT-08-01, University of Illinois at Urbana-Champaign (2008)
23. M. Tomassini, Spatially Structured Evolutionary Algorithms (Springer, Berlin, 2005)
24. Q. Yu, C. Chen, Z. Pan, Parallel Genetic Algorithms on Programmable Graphics Hardware, vol. 3612 (2005), pp. 1051-1059