Solving very large instances of the scheduling of independent tasks problem on the GPU

• Published in: Journal of parallel and distributed computing Vol. 73; no. 1; pp. 101 - 110
• Main Authors: Pinel, Frédéric, Dorronsoro, Bernabé, Bouvry, Pascal
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Amsterdam Elsevier Inc 01-01-2013; Elsevier
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Cellular genetic algorithm; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Exact sciences and technology; GPU; Scheduling; Software; Theoretical computing; GPU; Cellular genetic algorithm; Scheduling; High performance; Parallel algorithm; Task scheduling; Cellular algorithm; Computational geometry; Genetic algorithm; Graphic processing unit; Sequential method; Heuristic method; Massive parallelism; Central unit
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2012.02.018

In this paper, we present two new parallel algorithms to solve large instances of the scheduling of independent tasks problem. First, we describe a parallel version of the Min–min heuristic. Second, we present GraphCell, an advanced parallel cellular genetic algorithm (CGA) for the GPU. Two new generic recombination operators that take advantage of the massive parallelism of the GPU are proposed for GraphCell. A speedup study shows the high performance of the parallel Min–min algorithm in the GPU versus several CPU versions of the algorithm (both sequential and parallel using multiple threads). GraphCell improves state-of-the-art solutions, especially for larger problems, and it provides an alternative to our GPU Min–min heuristic when more accurate solutions are needed, at the expense of an increased runtime.
► Solving very large instances of the scheduling of independent tasks. ► New CPU and GPU multi-threaded parallel designs of Min–min. ► New GPU multi-threaded parallel design of a cellular genetic algorithm. ► New multi-purpose recombination operator for cellular genetic algorithms on GPU. ► Accurate and fast results.