数字信号处理应用程序执行时间变异性的定量研究

Yan Chao, Liu Ming
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引用次数: 0

摘要

在现代复杂数字信号处理平台上,任务执行时间具有不可预测性。本文提出了任务执行时间变异性的数学模型和定量研究方法。在现代复杂数字信号处理平台上,任务执行时间概率密度可以近似为正态分布。执行时间的均值方差(mean-variance)是衡量任务执行时间可变性程度的一个指标,它表示所有执行时间样本与平均执行时间的距离。本文分析了基于Godson 2E处理器的数字解调系统在任务执行时间上的可变性。实验表明,任务调度可以减少不同任务之间的交互。任务调度是显著降低任务执行时间均值方差的有效方法,是降低任务执行时间可变性程度的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative research on variability in the execution-time of digital signal processing applications
The task execution-time is unpredictability on the modern complex digital signal processing platform. This paper proposed the mathematical model and the quantitative research methods on the variability in the task execution-time. On the modern complex digital signal processing platform, the task execution-time probability density can be approximated as normal distribution. The mean-variance of execution-time, which can be an indicator to measure the degree of variability in the task execution-time, indicates the dispersion of all execution-time samples from the mean execution-time. This paper analyzed the variability in the task execution-time of the Godson 2E processor-based digital demodulation system. Experiments show that the interaction between different tasks will be reduced by task scheduling. Task scheduling is an effective method to significantly reduce the mean-variance of execution-time, and is an effective method to reduce the degree of variability in the task execution-time.
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