Advertisement

Parallel Cost Function Determination on GPU for the Job Shop Scheduling Problem

  • Wojciech Bożejko
  • Mariusz Uchroński
  • Mieczysław Wodecki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7204)

Abstract

The goal of this paper is to propose a methodology of the effective cost function determination for the job shop scheduling problem in parallel computing environment. Parallel Random Access Machine (PRAM) model is applied for the theoretical analysis of algorithm efficiency. The methods need a fine-grained parallelization, therefore the approach proposed is especially devoted to parallel computing systems with fast shared memory. The methods proposed are tested with CUDA and OpenCL and ran on NVidia and ATI GPUs.

Keywords

Operation Execution Disjunctive Graph Parallel Random Access Machine Crew PRAMs OpenCL Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bożejko, W.: A new class of parallel scheduling algorithms. Monographs series. Wroclaw University of Technology Publishing House (2010)Google Scholar
  2. 2.
    Bożejko, W., Pempera, J., Smutnicki, C.: Parallel Simulated Annealing for the Job Shop Scheduling Problem. In: Allen, G., Nabrzyski, J., Seidel, E., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2009, Part I. LNCS, vol. 5544, pp. 631–640. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Bożejko, W.: Solving the flow shop problem by parallel programming. Journal of Parallel and Distributed Computing 69, 470–481 (2009)CrossRefGoogle Scholar
  4. 4.
    Lawrence, S.: Resource constrained project scheduling: an experimental investigation of heuristic scheduling techniques. Graduate school of industrial administration. Carnegie Mellon University, Pittsburgh (1984)Google Scholar
  5. 5.
    Nowicki, E., Smutnicki, C.: A fast tabu search algorithm for the job shop problem. Management Science 42, 797–813 (1996)zbMATHCrossRefGoogle Scholar
  6. 6.
    Steinhöfel, K., Albrecht, A., Wong, C.K.: Fast parallel heuristics for the job shop scheduling problem. Computers & Operations Research 29, 151–169 (2002)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Taillard, E.D.: Benchmarks for basic scheduling problems. European Journal of Operational Research 64, 278–285 (1993)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Wojciech Bożejko
    • 1
  • Mariusz Uchroński
    • 1
    • 2
  • Mieczysław Wodecki
    • 3
  1. 1.Institute of Computer Engineering, Control and RoboticsWrocław University of TechnologyWrocławPoland
  2. 2.Wrocław Centre of Networking and SupercomputingWrocławPoland
  3. 3.Institute of Computer ScienceUniversity of WrocławWrocławPoland

Personalised recommendations