Memory requirements to balance thus asymptotically full-speedup FFT computation on processor arrays

J. Shieh
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引用次数: 1

Abstract

The paper proves that for a linearly-connected array of alpha processors or a mesh-connected array of alpha /sup 2/ processors, where each processor has computation bandwidth C, I/O bandwidth I and C/I=logm, Omega (m/sup alpha /) memory size is required in each processor to minimize the I/O requirement in balancing the FFT computation. Then it presents balanced FFT algorithms on these arrays to meet their memory size lower bounds. These algorithms are time optimal exhibiting full speedups.<>
内存需求平衡,因此渐近加速FFT计算在处理器阵列上
本文证明了对于alpha处理器线性连接阵列或alpha /sup 2/处理器网格连接阵列,其中每个处理器的计算带宽为C, I/O带宽为I,且C/I=logm,在平衡FFT计算时,每个处理器需要Omega (m/sup alpha /)内存大小以最小化I/O需求。然后在这些数组上提出平衡的FFT算法以满足它们的内存大小下界。这些算法是时间最优的,表现出完全的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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