An adaptative multi-GPU based branch-and-bound. A case study: The flow-shop scheduling problem

Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012

Volumn , Issue , 2012, Pages 389-395

  Chakroun, I ^a   Melab, N ^a  

^a UNIV LILLE   (France)

Author keywords

Branch and Bound Algorithms; Flow Shop Scheduling Problem; Multi GPU Computing; Parallel Bounding

Indexed keywords

AUTOTUNING; BOUNDING MODELS; BRANCH AND BOUNDS; BRANCH-AND-BOUND ALGORITHMS; COMBINATORIAL OPTIMIZATION PROBLEMS; COMPUTATIONAL POWER; COMPUTATIONAL RESOURCES; COMPUTING SYSTEM; FLOW SHOP PROBLEMS; FLOW SHOP SCHEDULING PROBLEM; GRAPHICS PROCESSING UNITS; LOWER BOUNDS; MULTI-GPU COMPUTING; PARALLEL BOUNDING; PARALLELIZING; PROBLEM INSTANCES; RUNTIMES; SIGNIFICANT IMPACTS; SUB-PROBLEMS;

ALGORITHMS; BRANCH AND BOUND METHOD; COMBINATORIAL OPTIMIZATION; COMPUTER GRAPHICS; EMBEDDED SOFTWARE; LAKES;

PROGRAM PROCESSORS;

EID: 84870429411     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPCC.2012.59     Document Type: Conference Paper

References (14)

1. M. J. Quinn. Analysis and implementation of branch-and-bound algorithms on a hypercube multicomputer. IEEE transactions on computers, Vol. 39, No3, pp. 384-387, 1990.
2. J.K. Lenstra, B.J. Lenstra, and A.H.G.R. Kan. A general bounding scheme for the permutation flow-shop problem. Operations Research, 26(1):53-67, 1978.
3. M. Mezmaz, N. Melab and E-G. Talbi. A Grid-enabled Branch and Bound Algorithm for Solving Challenging Combinatorial Optimization Problems. In Proc. of 21th IEEE Intl. Parallel and Distributed Processing Symp. (IPDPS), Long Beach, California, March 26th-30th, 2007.
4. R. Allen, L. Cinque, S. Tanimoto, L. Shapiro and D. Yasuda. A parallel algorithm for graph matching and its MasPar implementation. IEEE Transactions on Parallel and Distributed Systems, Vol. 8, No. 5, 1997.
5. L.G. Casadoa, J.A. Martneza, I. Garcaa and E.M.T. Hendrixb. Branch-and-Bound interval global optimization on shared memory multiprocessors. Optimization Methods and Software, Vol. 23, No.5, pp. 689-701, 2008.
6. CUDA C Best Practices Guide. http://developer.nvidia.com/nvidia- gpucomputing-documentation.
7. M. Djamai, B. Derbel and N. Melab. Distributed B&B: A Pure Peer-to-Peer Approach. In Proc. of IEEE IPDPS'2011, Woks. on Large-Scale Parallel Processing (LSPP), May 16-20, Anchorage (Alaska), 2011.
8. T-V. Luong, N. Melab and E-G. Talbi. GPU Computing for Parallel Local Search Metaheuristic Algorithms. IEEE Transactions on Computers, http://doi.ieeecomputersociety.org/10.1109/TC.2011.206, 2012.
9. A.Boukedjar, M.Lalami, D.El Baz. Parallel branch and bound on a CPU-GPU system. Euromicro International Conference on Parallel Distributed and Network-based Processing (PDP 2012), Garching (Allemagne), 15-17 Fvrier 2012, pp.392-398 Rapport LAAS N11471
10. B. Gendron and T.G. Crainic. Parallel Branch-and-Bound Algorithms: Survey and Synthesis. Operations Research, 42(06):1042-1066, 1994.
11. I. Chakroun, A. Bendjoudi and N. Melab. Reducing Thread Divergence in GPU-based B&B applied to the Flow-Shop Problem. In LNCS Proc. of 9th Intl. Conf. on Parallel Processing and Applied Mathematics (PPAM), 2011.
12. Jakub Kurzak, David A. Bader, and Jack Dongarra (eds.). Scientific Computing with Multicore and Accelerators, Chapman & Hall / CRC Press, 2010.
13. th Intl. Parallel Processing Symposium (IPPS), pp. 182-189, 1995.
14. E. Taillard. Taillard's FSP benchmarks. http://mistic.heigvd. ch/taillard/problemes.dir/ordonnancement.dir/ordonnancement.html.