实现PCA的面积和功耗高效寄存器分配技术

Sukhmani K. Thethi, Ravi Kumar
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引用次数: 0

摘要

本文在传统主成分分析方法的基础上,结合变量重用技术,提出了一种新的寄存器分配方法。PCA处理的是大维度的数据,是一种计算密集型的技术。本文的目的是在PCA的实施过程中避免寄存器切换,从而减少动态功耗和面积。在RC (cadence)工具中对两种技术编写的verilog代码进行了综合。仿制合成时,功率和面积分别大幅下降56.86.7%和56.66%;而在映射合成的情况下,与传统合成相比,所提出的技术功率显著降低86.145%,面积显著降低74.79%。
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Area and power efficient register allocation technique for the implementation of PCA
This paper presents a novel register allocation technique as well as the conventional technique for the implementation of Principal Component Analysis (PCA) incorporating variable reuse technique. PCA deals with a large dimensional data and is a computationally intensive technique. The purpose of this paper is to avoid register switching and hence reduction in dynamic power consumption as well as area during the implementation of PCA. Syntheses of verilog codes written for both the techniques were carried out in RC (cadence) tool. In case of generic synthesis, a substantial decrease of 56.867% in power and 56.66% in case of area was observed; whereas, in case of mapped synthesis, significant reduction of 86.145% in power and 74.79% in area was observed for the proposed technique in contrast to the conventional one.
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