Memory bounds for the distributed execution of a hierarchical Synchronous Data-Flow graph

K. Desnos, M. Pelcat, J. Nezan, Slaheddine Aridhi
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引用次数: 8

Abstract

This paper presents an application analysis technique to define the boundary of shared memory requirements of Multiprocessor System-on-Chip (MPSoC) in early stages of development. This technique is part of a rapid prototyping process and is based on the analysis of a hierarchical Synchronous Data-Flow (SDF) graph description of the system application. The analysis does not require any knowledge of the system architecture, the mapping or the scheduling of the system application tasks. The initial step of the method consists of applying a set of transformations to the SDF graph so as to reveal its memory characteristics. These transformations produce a weighted graph that represents the different memory objects of the application as well as the memory allocation constraints due to their relationships. The memory boundaries are then derived from this weighted graph using analogous graph theory problems, in particular the Maximum-Weight Clique (MWC) problem. State-of-the-art algorithms to solve these problems are presented and a heuristic approach is proposed to provide a near-optimal solution of the MWC problem. A performance evaluation of the heuristic approach is presented, and is based on hierarchical SDF graphs of realistic applications. This evaluation shows the efficiency of proposed heuristic approach in finding near optimal solutions.
分层同步数据流图分布式执行的内存边界
本文提出了一种应用分析技术,用于确定多处理器片上系统(MPSoC)在开发初期的共享内存需求边界。该技术是快速原型过程的一部分,并基于对系统应用程序的分层同步数据流(SDF)图描述的分析。分析不需要系统架构、映射或系统应用程序任务调度的任何知识。该方法的初始步骤包括对SDF图应用一组转换,以揭示其记忆特性。这些转换产生一个加权图,表示应用程序的不同内存对象以及由于它们之间的关系而产生的内存分配约束。然后使用类似的图论问题,特别是最大权重团(MWC)问题,从这个加权图中导出内存边界。提出了解决这些问题的最先进算法,并提出了一种启发式方法来提供MWC问题的近最优解。提出了一种基于实际应用的分层SDF图的启发式方法的性能评价方法。这个评价显示了所提出的启发式方法在寻找接近最优解方面的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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