An Appropriate Computing System and Its System Parameters Selection Based on Bottleneck Prediction of Applications

K. Komatsu, Takumi Kishitani, Masayuki Sato, Hiroaki Kobayashi
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引用次数: 1

Abstract

Recent computing systems have different characteristics as they consist of various processors such as a scalar processor, an accelerator, and a vector processor. As calculations patterns best suited for individual systems are different and diverged, it is difficult to determine in advance which computing system is appropriate when an application is given. Furthermore, due to the increase in the complexity of computing systems such as the many-core and new memory technologies, it is necessary to adjust many system parameters and find appropriate system parameters for each application to deliver the high performance of a computing system. One of the ways to find a computing system and its system parameter combinations suitable for an HPC application is a bruteforce approach of trial and error executions of an application on various computing systems and various system parameter combinations, which is no longer a realistic way due to its high cost of time and efforts. This paper proposes a method to carefully select a candidate of a computing system and system parameter combinations appropriate for executions of an HPC application by considering both characteristics of the application and computing systems. Thus, the proposed method can narrow down a large search space of computing systems and their system parameter combinations suitable for executing the HPC application.
基于应用瓶颈预测的合适计算系统及其系统参数选择
最近的计算系统具有不同的特点,因为它们由各种处理器组成,如标量处理器、加速器和矢量处理器。由于最适合于各个系统的计算模式是不同的和发散的,因此在给定应用程序时,很难预先确定哪种计算系统是合适的。此外,由于多核和新内存技术等计算系统复杂性的增加,需要调整许多系统参数,并为每个应用程序找到合适的系统参数,以提供计算系统的高性能。寻找适合HPC应用的计算系统及其系统参数组合的方法之一是在各种计算系统和各种系统参数组合上执行应用程序的试错方法,由于其高时间和精力成本,这种方法已不再是一种现实的方法。本文提出了一种方法,通过考虑应用程序和计算系统的特点,仔细选择适合执行高性能计算应用程序的候选计算系统和系统参数组合。因此,该方法可以缩小适合执行高性能计算应用的计算系统及其系统参数组合的大搜索空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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