Distributed task migration for thermal hot spot reduction in many-core microprocessors

In this paper, we propose a new distributed task migration method to reduce the thermal hot spots and on-chip temperature variance, which leads to better thermal reliability and reduced package costs of emerging many-core processors. The novelty of the new algorithm is that the task migration is done in a fully distributed way while we can still maintain some degrees of global view to guide the process. This is enabled by recently proposed distributed state tracking technique to dynamically estimate the average temperature of all the cores, which provides the important global view of the temperature of the whole chip to efficiently guide local task migration among cores. In addition, the local task migration will be carried out based on the power, temperature, and load influence from neighboring cores. Our experimental results on a 36 core microprocessor demonstrate that the proposed method can reduce 30% more thermal hot spots compared with the existing distributed thermal management method, leading to more balanced temperature distribution of many-core microprocessor chips.

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