Towards future adaptive multiprocessor systems-on-chip: An innovative approach for flexible architectures

F. Lemonnier, P. Millet, G. M. Almeida, M. Hübner, J. Becker, S. Pillement, O. Sentieys, Martijn Koedam, Shubhendu Sinha, K. Goossens, C. Piguet, M. Morgan, R. Lemaire
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引用次数: 24

Abstract

This paper introduces adaptive techniques targeted for heterogeneous manycore architectures and introduces the FlexTiles platform, which consists of general purpose processors with some dedicated accelerators. The different components are based on low power DSP cores and an eFPGA on which dedicated IPs can be dynamically configured at run-time. These features enable a breakthrough in term of computing performance while improving the on-line adaptive capabilities brought from smart heuristics. Thus, we propose a virtualisation layer which provides a higher abstraction level to mask the underlying heterogeneity present in such architectures. Given the large variety of possible use cases that these platforms must support and the resulting workload variability, offline approaches are no longer sufficient because they do not allow coping with time changing workloads. The upcoming generation of applications include smart cameras, drones, and cognitive radio. In order to facilitate the architecture adaptation under different scenarios, we propose a programming model that considers both static and dynamic behaviors. This is associated with self adaptive strategies endowed by an operating system kernel that provides a set of functions that guarantee quality of service (QoS) by implementing runtime adaptive policies. Dynamic adaptation will be mainly used to reduce both overall power consumption and temperature and to ease the problem of decreasing yield and reliability that results from submicron CMOS scales.
面向未来的自适应多处理器片上系统:灵活架构的创新方法
本文介绍了针对异构多核架构的自适应技术,并介绍了FlexTiles平台,该平台由通用处理器和一些专用加速器组成。不同的组件基于低功耗DSP内核和一个eFPGA,在其上可以在运行时动态配置专用ip。这些特性在提高智能启发式带来的在线自适应能力的同时,在计算性能方面实现了突破。因此,我们提出了一个虚拟化层,它提供了一个更高的抽象级别,以掩盖这种体系结构中存在的潜在异质性。考虑到这些平台必须支持大量可能的用例以及由此产生的工作负载可变性,离线方法不再足够,因为它们不允许处理随时间变化的工作负载。下一代应用包括智能相机、无人机和认知无线电。为了方便架构在不同场景下的适应,我们提出了一个同时考虑静态和动态行为的编程模型。这与操作系统内核赋予的自适应策略相关,该内核提供了一组功能,通过实现运行时自适应策略来保证服务质量(QoS)。动态自适应将主要用于降低整体功耗和温度,并缓解因亚微米CMOS尺度而导致的成品率和可靠性下降的问题。
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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