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We present a portable platform, called PIC_ENGINE, for acceleratingParticle-In-Cell (PIC) codes on heterogeneous many-core architectures such asGraphic Processing Units (GPUs). The aim of this development is efficientsimulations on future exascale systems by allowing different parallelizationstrategies depending on the application problem and the specific architecture.To this end, this platform contains the basic steps of the PIC algorithm andhas been designed as a test bed for different algorithmic options and datastructures. Among the architectures that this engine can explore, particularattention is given here to systems equipped with GPUs. The study demonstratesthat our portable PIC implementation based on the OpenACC programming model canachieve performance closely matching theoretical predictions. Using the CrayXC30 system, Piz Daint, at the Swiss National Supercomputing Centre (CSCS), weshow that PIC_ENGINE running on an NVIDIA Kepler K20X GPU can outperform theone on an Intel Sandybridge 8-core CPU by a factor of 3.4.

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC