Performance Optimization of Many-Core Systems by Exploiting Task Migration and Dark Core Allocation

نویسندگان

چکیده

As an effective scheme often adopted for performance tuning in many-core processors, task migration provides opportunity “hot” tasks to be migrated run on a “cool” core that has lower temperature. When needs migrate from one processor another, the can embark numerous modes defined by paths undertaken and/or destinations of migration. Selecting right mode shall follow always been difficult, and it more challenging with existence dark cores called back service (reactivated), which ushers additional modes. Previous works have demonstrated placed near active reduce power density so at higher voltage/frequency levels performance. However, existing schemes neither consider impact each application's performance, nor exploit trade-off under different Unlike schemes, this article, runtime algorithm simultaneously takes both into consideration is proposed, essentially two major steps. In first step, specific tied application whose need migrated, number determined overall maximized. The second step find appropriate region its location optimize communication latency computation performance; during focus reducing fragmentation free regions resulting Experimental results confirmed our approach achieves over 50 percent reduction total response time when compared recently proposed thermal-aware approachess.

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ژورنال

عنوان ژورنال: IEEE Transactions on Computers

سال: 2022

ISSN: ['1557-9956', '2326-3814', '0018-9340']

DOI: https://doi.org/10.1109/tc.2020.3042663