Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games are the so called Energy Games. Starting from a sequential baseline implementation, we investigate the use of massively data computation capabilities supported by modern GPUS to solve the initial credit problem for Energy Games. We present different parallel implementations on multi-core CPU and GPU systems. Our solution outperforms the baseline implementation by up to 36x speedup and obtains a faster convergence time on real-world graphs.
Accelerating energy games solvers on modern architectures
Formisano Andrea
;Gentilini Raffaella;
2017-01-01
Abstract
Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games are the so called Energy Games. Starting from a sequential baseline implementation, we investigate the use of massively data computation capabilities supported by modern GPUS to solve the initial credit problem for Energy Games. We present different parallel implementations on multi-core CPU and GPU systems. Our solution outperforms the baseline implementation by up to 36x speedup and obtains a faster convergence time on real-world graphs.File in questo prodotto:
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