一个近似精确的多处理器片上系统平台

A. S. Baroughi, Sini Huemer, H. Shahhoseini, N. Taherinejad
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引用次数: 1

摘要

由于计算任务的复杂性不断增加,提高效率的新兴计算范式,如近似计算,正在获得动力。然而,到目前为止,大多数提出的基于硬件的近似解决方案都是特定于应用程序和/或限于计算系统的较小单元,并且需要工程努力集成到系统的其余部分。本文提出了近似和精确的多处理器片上系统(AxE)平台。AxE是第一个通用的近似多处理器片上系统(MPSoC)。AxE是一个异构RISC-V平台,具有精确和近似的核心,允许探索任何应用程序的硬件近似和使用软件指令。利用整个MPSoC的全部容量,特别是像AxE这样的异构MPSoC,是一个越来越具有挑战性的问题。因此,我们还提出了一种任务映射方法,用于在AxE上运行精确和近似应用程序。这是一种混合任务映射,其中应用程序被视为一组任务,这些任务可以在具有不同功能(精确或近似)的不同处理器上独立运行。我们在AxE上评估了我们提出的方法,在三种混合工作负载上实现了32%的平均执行速度提升和21%的能耗节约,平均准确率达到99.3%。我们还在AxE上运行了一个示例图像处理应用程序,即灰度过滤器,并将展示其结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AxE: An Approximate-Exact Multi-Processor System-on-Chip Platform
Due to the ever-increasing complexity of computing tasks, emerging computing paradigms that increase efficiency, such as approximate computing, are gaining momentum. However, so far, the majority of proposed solutions for hardware-based approximation have been application-specific and/or limited to smaller units of the computing system and require engineering effort for integration into the rest of the system. In this paper, we present Approximate and Exact Multi-Processor system-on-chip (AxE) platform. AxE is the first general-purpose approximate Multi-Processor System-on-Chip (MPSoC). AxE is a heterogeneous RISC-V platform with exact and approximate cores that allows exploring hardware approximation for any application and using software instructions. Using the full capacity of an entire MPSoC, especially a heterogeneous one such as AxE, is an increasingly challenging problem. Therefore, we also propose a task mapping method for running exact and approximable applications on AxE. That is a mixed task mapping, in which applications are viewed as a set of tasks that can be run independently on different processors with different capabilities (exact or approximate). We evaluated our proposed method on AxE and reached a 32% average execution speed-up and 21% energy consumption saving with an average of 99.3% accuracy on three mixed workloads. We also ran a sample image processing application, namely gray-scale filter, on AxE and will present its results.
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