摘要
高端容错计算机的TPC-C性能测试由于成本高昂且时间漫长,导致市场上只有少部分产品进行了该项测试,无法满足生产商和购买者的需求,高端容错计算机领域需要一种简便快捷、低成本的TPC-C性能估算方法.文中分析了影响TPC-C性能的各种因素,以近5年来发布了TPC-C测试结果的服务器为样本,利用数理统计的方法,在服务器TPC-C性能与硬件指标之间建立了线性回归模型.优化后的模型估算精度达到95%以上,在一定程度上解释了服务器的硬件指标与TPC-C性能之间的因果关系,具备了方便准确地估算TPC-C性能的现实意义.文中所提出的将数理统计的方法用于TPC-C性能估算的思路以及搜集的大量相关数据,对今后该项研究具有重要意义.
As the TPC-C performance test of high-end fault-tolerant computer cost expensively and long time, only a small part of the products on the market do the test, which can not meet the needs of producers and buyers. A simple, efficient and low-cost method for estimating the TPC-C performance is widely needed. This paper analyzes the various factor affecting the TPC-C performance, establishes a linear regression model between the TPC-C performance and hardware indicators using the method of mathematical statistics. The model takes the TPC-C test results released in the past five years as the sample. After tuning, the estimating accuracy of the model is more than 95%. The model explains the causal relationship between the server＇s hardware indica- tors and TPC-C performance to some extent, and estimates the TPC-C performance conveniently and accurately. The idea that using mathematical statistics for TPC-C performance estimation and the large volume of data collected has important significance for future study.
出处
《计算机学报》
EI
CSCD
北大核心
2013年第6期1267-1279,共13页
Chinese Journal of Computers
基金
国家"八六三"高技术研究发展计划项目"地球系统模式中MPMD程序的调试
分析与高可用技术研究"(2010AA012403)
国家自然科学基金项目"基于进程相似性的大规模并行程序在线可扩展分析方法研究"(61103021)资助
Our group undertake 863 project"The Assessment and Measurement of High-End Fault-Tolerant Computer"
and has designed and optimized the TPC-C testing system(2010AA012403)
关键词
TPC-C
性能估算
多元线性回归
硬件指标
TPC-C
performance estimation
multi-factor linear regression
hardware indicators
