Abstract
In this paper we present initial results for implementing a constraint programming solver on a massively parallel supercomputer where coordination between processing elements is achieved through message passing. Previous work on message passing based constraint programming has been targeted towards clusters of computers (see [1,2] for some examples). Our target hardware platform is the IBM Blue Gene supercomputer. Blue Gene is designed to use a large number of relatively slow (800MHz) processors in order to achieve lower power consumption, compared to other supercomputing platforms. Blue Gene/P, the second generation of Blue Gene, can run continuously at 1 PFLOPS and can be scaled to 884,736-processors to achieve 3 PFLOPS performance. We present a dynamic scheme for allocating sub-problems to processors in a parallel, limited discrepancy tree search [3]. We evaluate this parallelization scheme on resource constrained project scheduling problems from PSPLIB [4].
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Keywords
- Search Tree
- Parallelization Scheme
- Master Process
- Resource Constrain Project Schedule Problem
- Tree Search Algorithm
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References
Michel, L., See, A., Van Hentenryck, P.: Transparent parallelization of constraint programming. INFORMS Journal of Computing (2009)
Duan, L., Gabrielsson, S., Beck, J.: Solving combinatorial problems with parallel cooperative solvers. In: Ninth International Workshop on Distributed Constraint Reasoning (2007)
Harvey, W.D., Ginsberg, M.L.: Limited discrepancy search. In: 14th International Joint Conference on Artificial Intelligence (1995)
Kolisch, R., Sprecher, A.: PSPLIB - a project scheduling library. European Journal of Operational Research 96, 205–216 (1996)
Bordeaux, L., Hamadi, Y., Samulowitz, H.: Experiments with massively parallel constraint solving. In: Twenty-first International Joint Conference on Artificial Intelligence, IJCAI 2009 (2009)
Blumofe, R.D., Joerg, C.F., Bradley, C.K., Leiserson, C.E., Randall, K., Zhou, Y.: Cilk: An efficient multithreaded runtime system. In: Proceedings of the Fifth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 207–216 (1995)
Michel, L., See, A., Van Hentenryck, P.: Parallelizing constraint programs transparently. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 514–528. Springer, Heidelberg (2007)
Baptiste, P., Pape, C.L., Nuijten, W.: Constraint-Based Scheduling - Applying Constraint Programming to Scheduling Problems. International Series in Operations Research and Management Science. Springer, Heidelberg (2001)
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Xie, F., Davenport, A. (2010). Massively Parallel Constraint Programming for Supercomputers: Challenges and Initial Results. In: Lodi, A., Milano, M., Toth, P. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2010. Lecture Notes in Computer Science, vol 6140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13520-0_36
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DOI: https://doi.org/10.1007/978-3-642-13520-0_36
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