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arXiv 1803.04786cs.DCcs.AR
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多核处理器参数优化的设计空间探索方法

A Design Space Exploration Methodology for Parameter Optimization in Multicore Processors

Prasanna Kansakar, Arslan Munir

摘要:

对于多核/众核处理平台的特定于应用的设计的需要随着计算系统在不同的应用领域中的使用而变得明显。为了使多核/众核处理器适合于应用特定的要求,必须相应地调整大量处理器设计参数,这涉及在大的搜索空间上进行严格和广泛的设计空间探索。在本文中,我们提出了一个有效的设计空间探索的方法。我们评估我们的方法在两个搜索空间-小和大,使用周期精确模拟器(ESESC)和一组标准的PARSEC和SPLASH-2基准。对于较小的设计空间,我们比较从我们的设计空间探索方法获得的结果,从完全穷举搜索。结果表明,从我们的方法得到的解决方案的质量是从完全穷举搜索得到的结果的1.35% - 3.69%,而只有探索2.74% - 3%的设计空间。对于更大的设计空间,我们比较解决方案的质量不同的结果,通过改变可调处理器的设计参数的数量,包括在我们的方法的穷举搜索阶段。结果表明,包括更多的可调参数在我们的方法的穷举搜索阶段大大提高了解决方案的质量。

英文摘要:

The need for application-specific design of multicore/manycore processing platforms is evident with computing systems finding use in diverse application domains. In order to tailor multicore/manycore processors for application specific requirements, a multitude of processor design parameters have to be tuned accordingly which involves rigorous and extensive design space exploration over large search spaces. In this paper, we propose an efficient methodology for design space exploration. We evaluate our methodology over two search spaces - small and large, using a cycle-accurate simulator (ESESC) and a standard set of PARSEC and SPLASH-2 benchmarks. For the smaller design space, we compare results obtained from our design space exploration methodology with results obtained from fully exhaustive search. The results show that solution quality obtained from our methodology are within 1.35% - 3.69% of the results obtained from fully exhaustive search while only exploring 2.74% - 3% of the design space. For larger design space, we compare solution quality of different results obtained by varying the number of tunable processor design parameters included in the exhaustive search phase of our methodology. The results show that including more number of tunable parameters in the exhaustive search phase of our methodology greatly improves solution quality.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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