软实时应用的概率延迟预算

S. Ghiasi, Po-Kuan Huang
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引用次数: 0

摘要

与硬实时应用程序不同,软实时应用程序只需要保证在输入数据空间上的“预期延迟”。这种范式转变需要定制的统计设计技术来取代传统的悲观最坏情况分析方法。统计设计方法可以对设计空间进行真实的评估,并利用其随机特性来提高设计质量。提出了一种新的概率时间预算算法,该算法将应用程序的期望延迟约束转化为其组件的延迟约束。该算法基于该问题的数学性质,在期望延迟约束下确定应用程序的最优加权时间松弛。fpga上几种多媒体应用的基于核心的合成实验结果表明,平均能量和面积分别提高了20%和19%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic delay budgeting for soft realtime applications
Unlike their hard realtime counterparts, soft realtime applications are only expected to guarantee their "expected delay" over input data space. This paradigm shift calls for customized statistical design techniques to replace the conventional pessimistic worst case analysis methodologies. Statistical design methods can provide a realistic assessment of design space, and improve the design quality by exploiting its stochastic behavior. We present a novel probabilistic time budgeting algorithm that translates the application expected delay constraint into its components delay constraints. Our algorithm which is based on mathematical properties of the problem, determines the optimal maximum weighted timing relaxation of an application under expected delay constraint. Experimental results on core-based synthesis of several multi-media applications on FPGAs show about 20% and 19% average energy and area improvement, respectively
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