PHP:在更高抽象级别生成耗电模式

Rohini Gulve, Anshu Goel, Virendra Singh
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引用次数: 3

摘要

性能、面积和功率是设计周期中每一步都要考虑和优化的最重要因素。设计工程师通常需要了解这些因素,以便在设计策略上做出正确的决策。较低抽象级别的功率分析可以提供比较高抽象级别更准确的分析。最坏情况下的功率可以通过高活动模式生成来估计。然而,随着模块或设计组件数量的增加,这种耗电模式(PHP)的生成变得具有挑战性。通过利用可用信息,可以在更高的抽象级别上加速此过程。在本文中,我们在更高的抽象层次上生成PHP,并显著提高了速度。采用遗传算法求出设计的全局最大功率。实验表明,实现的过程要快得多,并且发现PHP的功耗比随机生成的样本高10%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PHP: Power hungry pattern generation at higher abstraction level
The Performance, area, and power are most essential factors to be considered and optimize at every step in the design cycle. Design engineers often need to learn about these factors in order make right decisions on design strategies. Power analysis at lower levels of abstraction can provide more accurate analysis than higher levels. Worst case power can be estimated through high activity pattern generation. However, generation of such power hungry patterns (PHP) become challenging as the number of modules or design components increases. This process can be accelerated at higher abstraction levels by utilizing the available information. In this paper, we generate PHP by at higher abstraction level with significant speed up. A genetic algorithm is implemented to find out the global maximum power of designs. An experiment indicates that the process implemented is much faster and it finds about 10 % more power demanding PHP than random samples generated.
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