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A data-parallel implementation of O(N) hierarchical N-body methods

机译:O(N)分层N体方法的数据并行实现

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摘要

The O(N) hierarchical N-body algorithms and Massively Parallel Processors allow particle systems of 100 million particles or more to be simulated in acceptable time. We present a data-parallel implementation of Anderson's method and demonstrate both efficiency and scalability of the implementation on the Connection Machine CM-5/5E systems. The communication time for large particle systems amounts to about 10-25%, and the overall efficiency is about 35%. The evaluation of the potential field of a system of 100 million particles takes 3 minutes and 15 minutes on a 256 node CM-5E, giving expected four and seven digits of accuracy, respectively. The speed of the code scales linearly with the number of processors and number of particles.

机译:

O(N)分层N体算法和大规模并行处理器允许在可接受的时间内模拟1亿个或更多粒子的粒子系统。我们介绍了安德森方法的数据并行实现,并论证了连接机CM-5 / 5E系统上实现的效率和可扩展性。大粒子系统的通讯时间约为10-25%,总效率约为35%。在256个节点的CM-5E上,对1亿个粒子的系统的势场的评估分别需要3分钟和15分钟,分别给出了预期的四位数和七位数的准确度。代码的速度与处理器的数量和粒子的数量成线性比例。

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