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WHAT DO WE GAIN FROM HYPER-SYSTOLIC ALGORITHMS ON CLUSTER COMPUTERS?

机译:我们从集群计算机上的超收缩算法中学到了什么?

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摘要

The principle problem of parallel computing, the degradation of performance by internode-communication, is aggravated on modular cluster-architectures with off-board communication cards. In this contribution we consider so-called N-squared problems, the prototype being the N-body computation with long range interaction. We demonstrate that hyper-systolic algorithms are able to enhance the performance of such computations on parallel machines by alleviating the communication bottleneck, at the cost of moderately increased memory. We determine the efficiency of implementations on the Alpha-Linux-Cluster-Engine ALiCE at Wuppertal university compared to the SIMD system APE100.
机译:带有机外通信卡的模块化集群体系结构加剧了并行计算的原理问题,即节点间通信导致的性能下降。在这一贡献中,我们考虑了所谓的N平方问题,原型是具有远距离交互作用的N体计算。我们证明,超收缩算法能够缓解通信瓶颈,从而以适当增加内存的代价为代价,从而提高了并行计算机上此类计算的性能。与SIMD系统APE100相比,我们确定了伍珀塔尔大学Alpha-Linux-Cluster-Engine ALiCE上的实现效率。

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