Molecular Dynamics Simulation is an important method for acquiring liquid and solid atoms;properties. This method has been widely used in the fields of chemistry;physics;biology;medicine and materials. The complexity and ac curacy demand causes enormous workloads. Parallel computing is a feasible way to speedup large-scale molecular dy namics simulation. With hundreds of Gflops or even Tflops performance;GPU can speed up computing-intensive appli cations. This paper presented a parallel algorithm named oApT-AD;and we implemented it on GPU under OpenCL and CUDA Framework. The experiment results show that the oApT-AD algorithm can achieve 120 speedup on GPU Tesla C1060 under OpenCL Framework;compared to that on CPU. And we also implemented the oApT-AD algorithm on GPU under CUDA Framework. The implement under OpenCL Framework provides almost the same performance as the implement under CUDA Framework. Moreover;our algorithm can be extended to two or more GPUs;with good scala bility.%分子动力学模拟作为获得液体、固体性质的重要计算手段,广泛应用于化学、物理、生物、医药、材料等众多领域.模拟体系的复杂性和精确性的需求,使得计算量巨大,耗费时间长.并行计算是加速大规模分子动力学模拟的重要途径.GPU以几百GFlops甚至上TFlops的运算能力,为分子动力学模拟等的计算密集型应用提供了新的加速方案.提出了一种基于GPU的分子动力学模拟并行算法—oApT-AD,并在OpenCL和CUDA框架下加以实现.性能测试显示,在Tesla C1060显卡上,该算法在OpenCL框架下的实现相对于CPU的串行实现,最高达到120倍加速比.通过对比发现,该算法在CUDA上的性能与OpenCL基本相当.同时,该算法还可以扩展到两块及以上的GPU上,具有良好的可扩展性.
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