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The VEGA moderately parallel MIMD, moderately parallel SIMD, architecture for high performance array signal processing

机译:VEGA中度并行MIMD,中度并行SIMD,用于高性能阵列信号处理的架构

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摘要

In array radar signal processing applications, the processing demands range from tens of GFLOPS to several TFLOPS. To address this, as well as the, size and power dissipation issues, a special purpose “array signal processing” architecture is proposed. We argue that a combined MIMD-SIMD system can give flexibility, scalability, and programmability as well as high computing density. The MIMD system level, where SIMD modules are interconnected by a fiber-optic real-time network, provides the high level flexibility while the SIMD module level provides the compute density. In this paper we evaluate different design alternatives and show how the VEGA architecture was derived. By examining the applications and the algorithms used, the SIMD mesh processor is found be sufficient. However, the smaller the meshes are the better is the flexibility and efficiency. Then, based on prototype VLSI implementations and on instruction statistics, we find that a relatively large pipelined processing element maximises the performance per area. It is thereby concluded that the small SIMD mesh processor array with powerful processing elements is the best choice. These observations are further exploited in the design of the single-chip SIMD processor array to be included in the MIMD-style overall system. The system scales from 6.4 GFLOPS to several TFLOPS peak performance.
机译:在阵列雷达信号处理应用中,处理需求范围从几十个GFLOPS到几个TFLOPS。为了解决这个问题以及尺寸和功耗问题,提出了一种专用的“阵列信号处理”架构。我们认为,组合的MIMD-SIMD系统可以提供灵活性,可伸缩性,可编程性以及高计算密度。 SIMD模块通过光纤实时网络互连的MIMD系统级别提供了高级别的灵活性,而SIMD模块级别提供了计算密度。在本文中,我们评估了不同的设计替代方案,并展示了VEGA体系结构是如何派生的。通过检查应用程序和使用的算法,发现SIMD网格处理器就足够了。但是,网格越小,灵活性和效率越好。然后,基于原型VLSI实现和指令统计,我们发现相对较大的流水线处理元素可最大化单位面积的性能。由此得出结论,具有强大处理元素的小型SIMD网格处理器阵列是最佳选择。这些观察结果在单芯片SIMD处理器阵列的设计中得到了进一步利用,该阵列将包含在MIMD样式的整个系统中。系统从6.4 GFLOPS扩展到几个TFLOPS峰值性能。

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