Parallel Cost Function Determination on GPU for the Job Shop Scheduling Problem
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.
KeywordsOperation Execution Disjunctive Graph Parallel Random Access Machine Crew PRAMs OpenCL Implementation
Unable to display preview. Download preview PDF.
- 1.Bożejko, W.: A new class of parallel scheduling algorithms. Monographs series. Wroclaw University of Technology Publishing House (2010)Google Scholar
- 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
- 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