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FiberSCIP—A Shared Memory Parallelization of SCIP

Author

Listed:
  • Yuji Shinano

    (Zuse Institute Berlin, Berlin 14195, Germany)

  • Stefan Heinz

    (Fair Isaac Germany GmbH, Berlin 14195, Germany)

  • Stefan Vigerske

    (GAMS Software GmbH, Berlin 14195, Germany)

  • Michael Winkler

    (Gurobi GmbH, Berlin 14195, Germany)

Abstract

Recently, parallel computing environments have become significantly popular. In order to obtain the benefit of using parallel computing environments, we have to deploy our programs for these effectively. This paper focuses on a parallelization of SCIP (Solving Constraint Integer Programs), which is a mixed-integer linear programming solver and constraint integer programming framework available in source code. There is a parallel extension of SCIP named ParaSCIP, which parallelizes SCIP on massively parallel distributed memory computing environments. This paper describes FiberSCIP, which is yet another parallel extension of SCIP to utilize multi-threaded parallel computation on shared memory computing environments, and has the following contributions: First, we present the basic concept of having two parallel extensions, and the relationship between them and the parallelization framework provided by UG (Ubiquity Generator), including an implementation of deterministic parallelization. Second, we discuss the difficulties in achieving a good performance that utilizes all resources on an actual computing environment, and the difficulties of performance evaluation of the parallel solvers. Third, we present a way to evaluate the performance of new algorithms and parameter settings of the parallel extensions. Finally, we demonstrate the current performance of FiberSCIP for solving mixed-integer linear programs (MIPs) and mixed-integer nonlinear programs (MINLPs) in parallel.

Suggested Citation

  • Yuji Shinano & Stefan Heinz & Stefan Vigerske & Michael Winkler, 2018. "FiberSCIP—A Shared Memory Parallelization of SCIP," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 11-30, February.
    • Handle: RePEc:inm:orijoc:v:30:y:2018:i:1:p:11-30
    DOI: 10.1287/ijoc.2017.0762
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    References listed on IDEAS

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    1. Thorsten Koch & Ted Ralphs & Yuji Shinano, 2012. "Could we use a million cores to solve an integer program?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(1), pages 67-93, August.
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    3. R.E. Bixby & W. Cook & A. Cox & E.K. Lee, 1999. "Computational experience with parallel mixed integerprogramming in a distributed environment," Annals of Operations Research, Springer, vol. 90(0), pages 19-43, January.
    4. Y. Xu & T. K. Ralphs & L. Ladányi & M. J. Saltzman, 2009. "Computational Experience with a Software Framework for Parallel Integer Programming," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 383-397, August.
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