Concurrent FFT computing on multicore processors

被引:0
|
作者
Barhen, J. [1 ]
Humble, T. [1 ]
Mitra, P. [1 ,2 ]
Imam, N. [1 ]
Schleck, B. [3 ]
Kotas, C. [1 ]
Traweek, M. [4 ]
机构
[1] Oak Ridge Natl Lab, Comp Sci & Math Div, CESAR, Oak Ridge, TN 37831 USA
[2] Univ Notre Dame, Notre Dame, IN 46556 USA
[3] Coherent Logix Inc, Austin, TX 78746 USA
[4] Off Naval Res, Maritime Sensing Branch, Arlington, VA 22203 USA
来源
关键词
multicore processors; FFT; HyperX; IBM cell; transverse vectorization;
D O I
10.1002/cpe.1746
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The emergence of streaming multicore processors with multi-SIMD (single-instruction multiple-data) architectures and ultra-low power operation combined with real-time compute and I/O reconfigurability opens unprecedented opportunities for executing sophisticated signal processing algorithms faster and within a much lower energy budget. Here, we present an unconventional Fast Fourier Transform (FFT) implementation scheme for the IBM Cell, named transverse vectorization. It is shown to outperform (both in terms of timing and GFLOP throughput) the fastest FFT results reported to date for the Cell in the open literature. We also provide the first results for multi-FFT implementation and application on the novel, ultra-low power Coherent Logix HyperX processor. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:29 / 44
页数:16
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