Assessing Multi-task Placement Algorithms in RCUs

作者: Anita Tino , Kaamran Raahemifar

DOI: 10.1109/IPDPSW.2016.183

关键词:

摘要: In response to the current requirements of energy efficiency and high performance in computing systems, architects have turned towards customization. General purpose however remains a challenge as processors must adhere variety applications, on-chip resources, increased without solely relying on transistor scaling additional cache levels. For this reason, concept Reconfigurable Computing Unit (RCU) been proposed which redesign conventional processor microarchitectural architectural level. RCUs are extended work support multi-task workload using OmpSs, where task instruction placement algorithms thoroughly assessed for effects efficiency. Experimental results demonstrate that single RCU with double engine configuration is able exceed single-core average by 1.48x achieve/exceed dual-core performance. The various inter-and intra-task tested also display up 16.7% 23% fluctuation efficiency, respectively, depending method combination employed.

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