On the scalability of FFT on parallel computers

Abhishek Gupta, V. Kumar
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引用次数: 29

Abstract

The scalability of the parallel fast Fourier transform (FFT) algorithm on mesh- and hypercube-connected multicomputers is analyzed. The hypercube architecture provides linearly increasing performance for the FFT algorithm with an increasing number of processors and a moderately increasing problem size. However, there is a limit on the efficiency, which is determined by the communication bandwidth of the hypercube channels. Efficiencies higher than this limit can be obtained only if the problem size is increased very rapidly. Technology-dependent features, such as the communication bandwidth, determine the upper bound on the overall performance that can be obtained from a P-processor system. The upper bound can be moved up by either improving the communication-related parameters linearly or increasing the problem size exponentially. The scalability analysis shows that the FFT algorithm cannot make efficient use of large-scale mesh architectures. The addition of such features as cut-through routing and multicasting does not improve the overall scalability on this architecture.<>
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FFT在并行计算机上的可扩展性
分析了并行快速傅里叶变换(FFT)算法在网格连接和超立方体连接多计算机上的可扩展性。随着处理器数量的增加和问题大小的适度增加,超立方体体系结构为FFT算法提供了线性增长的性能。然而,效率是有限的,这是由超立方体信道的通信带宽决定的。只有当问题规模迅速增加时,才能获得高于此限制的效率。依赖于技术的特性,如通信带宽,决定了p处理器系统所能获得的总体性能的上限。上界可以通过线性改进通信相关参数或以指数方式增加问题大小来向上移动。可扩展性分析表明,FFT算法不能有效地利用大规模网格结构。添加直通路由和多播等功能并不能提高该架构的整体可扩展性。
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