大规模并行计算机系统性能测评体系

J4 ›› 2013, Vol. 35 ›› Issue (3): 25-30.

大规模并行计算机系统性能测评体系

刘杰，迟利华，蒋杰，徐涵，晏益慧，胡庆丰

（并行与分布处理国防科技重点实验室，湖南长沙 410073）

收稿日期:2011-05-16 修回日期:2011-08-20 出版日期:2013-03-25 发布日期:2013-03-25
基金资助:
国家863计划资助项目（2012AA01A301）；国家自然科学基金资助项目（60970033）

Performance evaluation methodology for
massively parallel computer systems

LIU Jie，CHI Lihua，JIANG Jie，XU Han，YAN Yihui,HU Qingfeng

（National Laboratory for Parallel and Distributed Processing,Changsha 410073,China）

Received:2011-05-16 Revised:2011-08-20 Online:2013-03-25 Published:2013-03-25

摘要/Abstract

摘要：

复杂的大规模并行计算机系统需要能客观反映系统性能的测评方法，单个指标难以全面评价系统的性能特点。从用户需求出发，给出了大规模并行计算机系统用户适用性概念，利用适用性概念，建立了大规模系统性能测评体系，包括总体适用性、分项适用性、适用性概念、准则和Benchmark程序。整个测评体系尽量消除主观因素，做到客观定量，利用测评体系，借助性能分析数据获取工具，在得到量化的分项适用性的基础上，通过权重公式可以求出总体适用性，根据总体适用性的大小来判断不同大规模计算机系统是否满足用户的需求。

关键词: 性能测评, 大规模并行计算机系统, 用户适用性

Abstract:

The complexity of modern massively parallel computer systems requires sophisticated method to facilitate the evaluation of system performance, and it is difficult to measure all the characteristics of systems using a single metric. The concept of applicability is given from the demand of users for supercomputers. Based on the applicability concept, we present a performance evaluation methodology for massively parallel computer systems. The methodology, including total applicability, subentry applicability, the concepts of subentry, metrics and benchmarks, can avoid the personal factors and obtains the impersonality results for systems performance. After collecting data using performance analysis tools, the data can be used to get the subentry applicability. Then the total applicability can be calculated by the weight equation. Based on the total applicability, one can evaluate whether the massively parallel computer systems satisfy the demand of user or not.

Key words: performance evaluation;massively parallel computer system;applicability of user

刘杰，迟利华，蒋杰，徐涵，晏益慧，胡庆丰. 大规模并行计算机系统性能测评体系[J]. J4, 2013, 35(3): 25-30.

LIU Jie，CHI Lihua，JIANG Jie，XU Han，YAN Yihui,HU Qingfeng. Performance evaluation methodology for
massively parallel computer systems[J]. J4, 2013, 35(3): 25-30.