Toolchain integration of runtime variability and aging awareness in multicore platforms

Ramakrishna Nittala, Francesco Barchi, Gianvito Urgese, A. Acquaviva
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引用次数: 1

Abstract

The impact of process variations and wear-out mechanisms in current and next generation technology nodes is becoming relevant and cannot be compensated at the device or architectural level. Intra-die process variations raising at the core level and platform level makes parallel multicore platforms intrinsically heterogeneous, because the various cores are clocked at different operational frequencies. Power consumption becomes heterogeneous too, both considering dynamic and leakage consumption. Wear-out processes add further uncertainty over time. In this context, to fully exploit the computational capability of the platform parallelism, variability and wear-out aware task allocation strategies must be developed. In this work, we discuss techniques to perform task allocation and we show how they can be integrated in a software toolchain. We report results of the implementation of variability and wear-out awareness in stateof- art multicore platforms.
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多核平台中运行时可变性和老化意识的工具链集成
在当前和下一代技术节点中,工艺变化和损耗机制的影响正在变得相关,并且无法在设备或体系结构级别上得到补偿。内核级和平台级的芯片内工艺变化使得并行多核平台本质上是异构的,因为不同的内核以不同的工作频率进行时钟处理。考虑到动态和泄漏功耗,功耗也变得异构。随着时间的推移,损耗过程增加了进一步的不确定性。在这种情况下,为了充分利用平台并行性的计算能力,必须开发可变性和磨损感知任务分配策略。在这项工作中,我们讨论了执行任务分配的技术,并展示了如何将它们集成到软件工具链中。我们报告了在最先进的多核平台中实现可变性和磨损意识的结果。
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