  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 that recently gained interest are the so
called Energy Games. The fast-known algorithm solves Energy Games in O(EVW)
where W is the maximum weight. Starting from a sequential baseline
implementation, we investigate the use of massively data computation
capabilities supported by modern Graphics Processing Units to solve the
`initial credit problem' for Energy Games. We present four 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.
