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.
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