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RegionSeeker: Automatically Identifying and Selecting Accelerators From Application Source Code

机译:RegionSeeker:从应用程序源代码中自动识别和选择加速器

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Embedded systems present stringent and often conflicting requirements. On the one side, the need for high performance within a tight energy budget favors inflexible Application Specific Integrated Circuit (ASIC) implementations; on the other side, a short time-to-market demands programmability. Hybrid architectures such as special-purpose customized processors represent an attractive solution, as they arc programmable by software, but use dedicated hardware to accelerate parts of the computation. In such a scenario, the capability of automatically identifying the computation parts to he realized in hardware is highly desirable, in order to reduce design time and effort. This paper aims at advancing the state-of-the-art in this field. We recognize that subgraphs of control flow graphs having a single input control point and a single output control point, that we call regions, are good targets for the synthesis of application specific hardware accelerators. We therefore provide a method to identify them and an LINM-based toolchain (named RegionSeeker) that, analyzing a software application, automatically selects its most profitable regions given an area constraint. Experimental evidence shows that the accelerators identified by RegionSeeker provide a speedup of up to 4.6x and, on average, approximately 30% higher speedup is achieved compared to state-of-the-art identification techniques.
机译:嵌入式系统提出了严格且经常相互冲突的要求。一方面,在紧凑的能源预算内对高性能的需求偏向于不灵活的专用集成电路(ASIC)实施;另一方面,上市时间短需要可编程性。诸如专用定制处理器之类的混合体系结构代表了一种有吸引力的解决方案,因为它们可以通过软件进行编程,但是使用专用硬件来加速部分计算。在这种情况下,非常需要能够自动识别要在硬件中实现的计算部件的能力,以减少设计时间和工作量。本文旨在推动该领域的最新发展。我们认识到,具有单个输入控制点和单个输出控制点的控制流程图的子图(我们称为区域)是综合专用硬件加速器的良好目标。因此,我们提供了一种识别它们的方法以及一个基于LINM的工具链(名为RegionSeeker),该工具链在分析软件应用程序时会根据区域限制自动选择其最有利可图的区域。实验证据表明,与最先进的识别技术相比,RegionSeeker识别的加速器可提供高达4.6倍的加速,并且平均可实现约30%的加速。

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