StreaMorph:一个使用高级抽象综合节能自适应程序的案例

D. Bui, Edward A. Lee
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引用次数: 12

摘要

本文提出了自适应程序的概念,它的计算和通信结构可以根据环境和需求的变化而变化,从而节省能源和计算资源。在这种方法中,程序员使用更高抽象层次的语言编写单个程序。编译器将利用抽象的属性来生成一个自适应程序,该程序能够根据环境和需求的变化调整计算和通信结构。我们开发了一种称为StreaMorph的技术,它利用流程序的同步数据流(SDF)编程模型的属性来实现运行时流图转换。StreaMorph技术可用于优化内存使用,并通过关闭空闲内核或降低工作频率来调整内核利用率,从而降低能耗。这种运行时转换的主要挑战是通过复制不同流图结构之间的状态来保持一致的程序状态,因为针对不同核数优化的流程序通常具有不同的过滤器集和过滤器间通道。我们提出了一种分析方法,通过最小化基于SDF模型属性的状态复制来帮助简化程序状态复制过程。最后,我们在StreamIt编译器中实现StreaMorph方法。我们在英特尔至强E5450上的实验表明,使用StreaMorph将使用的核数从8核减少到1核,例如当流式传输速率降低时,可以平均减少76.33%的能耗。使用StreaMorph将工作负载从四核扩展到六核或七核,例如,当有更多的核可用时,为了降低操作频率,可以减少10%的能量。此外,当从8核切换到1核时,与直接的核间过滤器迁移技术相比,StreaMorph可以使缓冲区大小减少82.58%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
StreaMorph: A case for synthesizing energy-efficient adaptive programs using high-level abstractions
This paper presents the concept of adaptive programs, whose computation and communication structures can morph to adapt to environmental and demand changes to save energy and computing resources. In this approach, programmers write one single program using a language at a higher level of abstraction. The compiler will exploit the properties of the abstractions to generate an adaptive program that is able to adjust computation and communication structures to environmental and demand changes. We develop a technique, called StreaMorph, that exploits the properties of stream programs' Synchronous Dataflow (SDF) programming model to enable runtime stream graph transformation. The StreaMorph technique can be used to optimize memory usage and to adjust core utilization leading to energy reduction by turning off idle cores or reducing operating frequencies. The main challenge for such a runtime transformation is to maintain consistent program states by copying states between different stream graph structures, because a stream program optimized for different numbers of cores often has different sets of filters and inter-filter channels. We propose an analysis that helps simplify program state copying processes by minimizing copying of states based on the properties of the SDF model. Finally, we implement the StreaMorph method in the StreamIt compiler. Our experiments on the Intel Xeon E5450 show that using StreaMorph to minimize the number of cores used from eight cores to one core, e.g. when streaming rates become lower, can reduce energy consumption by 76.33% on average. Using StreaMorph to spread workload from four cores to six or seven cores, e.g. when more cores become available, to reduce operating frequencies, can lead to 10% energy reduction. In addition, StreaMorph can lead to a buffer size reduction of 82.58% in comparison with a straightforward inter-core filter migration technique when switching from using eight cores to one core.
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