QoS management on heterogeneous architecture for parallel applications


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Quality of service (QoS) management is widely employed to provide differentiable performance to programs with distinctive priorities on conventional chip multi-processor (CMP) platforms. Recently, heterogeneous architecture integrating diverse processor cores on the same silicon has been proposed to better serve various application domains and it is expected to be an important design paradigm of future processors. Therefore, the QoS management on emerging heterogeneous systems will be of great significance. On the other hand, parallel applications are becoming increasingly important in modern computing community in order to explore the benefit of thread-level parallelism on CMPs. However, considering the diverse characteristics of thread synchronization, data sharing, and parallelization pattern, governing the execution of multiple parallel programs with different performance requirements becomes a complicated yet significant problem. In this paper, we study QoS management for parallel applications running on heterogeneous CMP systems. We comprehensively assess a series of task-to-core mapping policies on a real heterogeneous hardware (QuickIA) by characterizing their impacts on performance of individual applications. Our evaluation results show that the proposed QoS policies are effective to improve the performance of programs with highest priority while striking good tradeoff with system fairness.
real heterogeneous hardware,parallel processing,heterogeneous architecture,quality-of-service,quality of service,parallelization pattern,processor cores,quality of service management,chip multiprocessor platforms,multiprocessing systems,task-to-core mapping policies,Heterogeneous,QoS policies,thread-level parallelism,QoS management,parallel applications,thread synchronization,QuickIA,CMP platforms,parallel application,data sharing
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