Power-Efficient Predication Techniques for Acceleration of Control Flow Execution on CGRA
Power-Efficient Predication Techniques for Acceleration of Control Flow Execution on CGRA
复制标题
用于加速 CGRA 上控制流执行的节能预测技术
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Kiyoung Choi
中科院分区：
文献类型：
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作者：
Kyuseung Han;Junwhan Ahn;Kiyoung Choi
粗粒度可重构架构通常具有由集中单元控制的处理元件阵列。这使得在没有预测的情况下执行PE之间具有控制分歧的程序变得困难。然而，由于较长的指令字和不必要的取指令解码无效步骤，传统的预测技术对性能和功耗都有负面影响。本文揭示了谓词执行中尚未得到很好解决的性能和功耗问题。此外，它提出了快速且节能的预测机制。通过门级仿真进行的实验表明，我们的机制将能量延迟积平均提高了 11.9% 至 23.8%。
Coarse-grained reconfigurable architecture typically has an array of processing elements which are controlled by a centralized unit. This makes it difficult to execute programs having control divergence among PEs without predication. However, conventional predication techniques have a negative impact on both performance and power consumption due to longer instruction words and unnecessary instruction-fetching decoding nullifying steps. This article reveals performance and power issues in predicated execution which have not been well-addressed yet. Furthermore, it proposes fast and power-efficient predication mechanisms. Experiments conducted through gate-level simulation show that our mechanism improves energy-delay product by 11.9% to 23.8% on average.