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Performance Optimal Online DVFS and Task Migration Techniques for Thermally Constrained Multi-Core Processors

机译:热约束多核处理器的性能最佳在线DVFS和任务迁移技术

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摘要

Extracting high performance from multi-core processors requires increased use of thermal management techniques. In contrast to offline thermal management techniques, online techniques are capable of sensing changes in the workload distribution and setting the processor controls accordingly. Hence, online solutions are more accurate and are able to extract higher performance than the offline techniques. This paper presents performance optimal online thermal management techniques for multicore processors. The techniques include dynamic voltage and frequency scaling and task-to-core allocation or task migration. The problem formulation includes accurate power and thermal models, as well as leakage dependence on temperature. This paper provides a theoretical basis for deriving the optimal policies and computationally efficient implementations. The effectiveness of our DVFS and task-to-core allocation techniques are demonstrated by numerical simulations. The proposed task-to-core allocation method showed a 20.2% improvement in performance over a power-based thread migration approach. The techniques have been incorporated in a thermal-aware architectural-level simulator called MAGMA that allows for design space exploration, offline, and online dynamic thermal management. The simulator is capable of handling simulations of hundreds of cores within reasonable time.
机译:从多核处理器中提取高性能需要更多使用热管理技术。与离线热管理技术相比,在线技术能够感知工作负载分布的变化并相应地设置处理器控制。因此,在线解决方案比离线技术更准确,并且能够提取更高的性能。本文介绍了用于多核处理器的性能最佳的在线热管理技术。这些技术包括动态电压和频率缩放以及任务到核心的分配或任务迁移。问题公式包括准确的功率和热模型,以及对温度的泄漏依赖性。本文为推导最优策略和高效计算实现提供了理论基础。数值模拟证明了我们的DVFS和任务到核心分配技术的有效性。与基于功能的线程迁移方法相比,建议的任务到核心分配方法在性能上提高了20.2%。该技术已被整合到称为MAGMA的热感知架构级仿真器中,该仿真器允许进行设计空间探索,离线和在线动态热管理。该仿真器能够在合理的时间内处理数百个内核的仿真。

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