A unified framework for throughput analysis of synchronous data flow graphs under memory constraints: work-in-progress

Xue-Yang Zhu
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Abstract

Streaming applications are often modeled with Synchronous data flow graphs (SDFGs). A proper analysis of the models is helpful to predict the performance of a system. In this paper, we focus on the throughput analysis of memory-constrained SDFGs (MC SDFGs), which needs to choose a memory abstraction that decides when the space of consumed data is released and when the required space is claimed. Different memory abstractions may lead to different achievable throughputs. The existing techniques, however, consider only a certain abstraction. If a model is implemented according to other abstractions, the analysis result may not truly evaluate the performance of the system. In this paper, we present a unified framework for throughput analysis of MC SDFGs for difference abstractions, aiming to provide evaluations matching up to the corresponding implementations.
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用于在内存约束下同步数据流图的吞吐量分析的统一框架:正在进行的工作
流应用程序通常使用同步数据流图(sdfg)建模。对这些模型进行适当的分析有助于预测系统的性能。在本文中,我们关注内存约束sdfg (MC sdfg)的吞吐量分析,它需要选择一个内存抽象来决定何时释放消耗数据的空间以及何时要求所需的空间。不同的内存抽象可能导致不同的可实现吞吐量。然而,现有的技术只考虑某种抽象。如果模型是根据其他抽象实现的,那么分析结果可能无法真正评估系统的性能。在本文中,我们提出了一个统一的框架来分析不同抽象的MC sdfg的吞吐量,旨在提供与相应实现相匹配的评估。
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