基于微线程级并行的原子流计算单元

Nasim Farahini, A. Hemani
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引用次数: 2

摘要

对更高分辨率图像和通信带宽的需求日益增长,要求流媒体应用程序处理不断增长的数据集大小。此外,与计算成本相比,随着技术的扩展,移动数据的成本正在以较慢的速度降低。这些趋势促使人们提出了流处理器的微架构重组,将流计算分为功能计算、地址约束计算和地址生成,并部署独立的分布式微线程来实现它们。该方案是在指令级并行化它们的替代方案。该方案具有两个优点:一个更有效的序列逻辑,以及在地址生成和传输中节省能源。对一组流应用程序的这些好处进行了量化,结果显示,顺序器逻辑的硅效率平均提高了39%,总计算效率提高了23%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Atomic stream computation unit based on micro-thread level parallelism
The increasing demand for higher resolution of images and communication bandwidth requires the streaming applications to deal with ever increasing size of datasets. Further, with technology scaling the cost of moving data is reducing at a slower pace compared to the cost of computing. These trends have motivated the proposed micro-architectural reorganization of stream processors by dividing the stream computation into functional computation, address constraints computation and address generation and deploying independent, distributed micro-threads to implement them. This scheme is an alternative to parallelizing them at instruction level. The proposed scheme has two benefits: a more efficient sequencer logic and energy savings in address generation and transportation. These benefits are quantified for a set of streaming applications and show average percentage improvement of 39 in silicon efficiency of the sequencer logic and 23 in total computational efficiency.
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