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NSGA-II-Based Design Space Exploration for Energy and Throughput Aware Multicore Architectures

机译:基于NSGA-II的能源和吞吐量感知多核架构的设计空间探索

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Multicore architectures are mainstream due to ever increasing demand of throughput by modern applications. However, the suboptimal utilization of available resources in these architectures may imply an inevitable energy overhead. This energy overhead can only be avoided if the multicore systems support reconfiguration of available resources as per application demand. To achieve the target objectives (i.e., Energy efficiency with Throughput maximization) in multicore systems, many decision variables need to be optimized or analyzed to find the better trade-off. Heuristic-based approaches are aimed to provide a good-enough solution instead of a lengthy exhaustive search. This paper presents an Evolutionary Algorithm (EA)-based approach, i.e., Nondomi-nated Sorting Genetic Algorithm-ll (NSGA-II). Three decision variables, i.e., number of cores, cache size and frequency are used to find best solution. The proposed approach is validated over a set of parallel benchmarks using a cycle accurate simulator. The results show a significant amount of energy saving along with minimal impact on the throughput of the system.
机译:由于现代应用对吞吐量的日益增长的需求,多核体系结构已成为主流。但是,这些体系结构中可用资源的次优利用可能意味着不可避免的能源开销。仅当多核系统支持根据应用程序需求重新配置可用资源时,才能避免这种能源开销。为了在多核系统中实现目标目标(即通过吞吐量最大化的能源效率),需要优化或分析许多决策变量以找到更好的折衷方案。基于启发式的方法旨在提供足够好的解决方案,而不是冗长的详尽搜索。本文提出了一种基于进化算法(EA)的方法,即非分类排序遗传算法II(NSGA-II)。使用三个决策变量,即内核数,缓存大小和频率来找到最佳解决方案。使用周期精确模拟器在一组平行基准上对提出的方法进行了验证。结果表明,可节省大量能源,并且对系统吞吐量的影响最小。

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