超高性能,低功耗,数据并行雷达实现

S. Reddaway, P. Bruno, R. Pancoast, P. Rogina
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引用次数: 6

摘要

雷达涉及应用于大量数据的类似操作。因此,它非常适合于数据并行(SIMD)硬件。过去,大型数据并行机已应用于雷达,但收效甚微。这是由于编程问题、成本以及对于大多数嵌入式应用程序来说硬件太大等原因造成的。大多数SIMD机器在十年前就消失了。现在有了新一代的SIMD COTS技术,具有强大的处理元件(pe)和浮点硬件。WorldScape正在将这些芯片应用于雷达处理,并在更低的功耗(GFLOPS/Watt)下展示了显著提高的性能。这些实现为传统的FPGA和DSP解决方案提供了有吸引力的替代方案。洛克希德-马丁公司已经为这些实现提供了基准验证测试和支持。目前的实现是基于ClearSpeed Technology PLC提供的64 PE, 25 GFLOP CS-301芯片。WorldScape演示了FFT、脉冲压缩、QR分解的一种形式,以及在这一代硬件上使用c级编程和优化汇编的其他应用程序。下一代芯片是兼容的,但也有一些改进,将显著提高I/O性能和原始GFLOP吞吐量。WorldScape和洛克希德-马丁公司展示了最新的演示,并讨论了嵌入式雷达处理的可扩展处理平台,该平台显着提高了I/O性能,并为技术插入提供了政府合格硬件的路线图。讨论了体系结构、数据并行编码方法、可扩展处理平台的附加功能以及与嵌入式防御雷达应用的相关性。
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Ultra-high performance, low-power, data parallel radar implementations
Radar involves similar operations applied to large amounts of data. It is thus well suited to data parallel (SIMD) hardware. In the past, large data-parallel machines have been applied to radar with limited success. This has been due to such reasons as programming issues, cost, and the hardware being too big for most embedded applications. Most SIMD machines went away a decade ago. There is now a new generation of SIMD COTS technology with powerful processing elements (PEs) and floating-point hardware. WorldScape is applying these chips to radar processing, and has demonstrated significantly more performance with much lower power dissipation (GFLOPS/Watt). These implementations provide attractive alternatives to traditional FPGA and DSP solutions. Lockheed-Martin has provided benchmark validation testing and support for these implementations. The current implementation is based on a 64 PE, 25 GFLOP CS-301 chip supplied by ClearSpeed Technology PLC. WorldScape has demonstrated FFT, pulse compression, a form of QR factorization, and other applications on this generation of hardware using a mix of C-level programming and optimized assembly. The next generation chip is compatible, but also has several improvements that will significantly enhance I/O performance as well as raw GFLOP throughput. WorldScape and Lockheed-Martin presents the updated demonstrations and discuss a scalable processing platform for embedded radar processing which significantly improves I/O performance and provides a roadmap to government-qualified hardware for technology insertion. Architectures, data parallel coding approaches, additional functionality of the scalable processing platform, and relevance to embedded defense radar applications is discussed.
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