基于实验技术的计算机系统性能测试与评估方法研究  

Research on performance testing and evaluation method for computer system based on experimental technique

在线阅读下载全文

作  者:李钊 LI Zhao(Xi̓an Mingde Institute of Technology,Xi̓an 710124,China)

机构地区:[1]西安明德理工学院,西安710124

出  处:《计算机应用文摘》2025年第6期253-255,258,共4页

摘  要:作为一种科学的测试手段,实验技术可以帮助研究人员深入分析系统的各项性能指标,从而为系统优化提供依据。文章将探讨如何利用实验技术来测试和评估计算机系统性能,主要包括实验设计、测试环境的搭建、测试指标的选择、数据的采集与分析等方面。首先,合理的实验设计能够确保测试结果的准确性与可靠性。通过模拟不同的工作负载和实际应用场景,可以评估系统在不同情况下的表现。其次,搭建稳定且符合测试需求的测试环境是确保测试结果一致性和重现性的关键。测试指标的选择应综合考虑计算机系统的处理能力、响应时间、吞吐量、负载均衡等因素。最后,数据采集与分析要采用科学的统计方法,以提取有价值的信息,发现潜在的性能瓶颈,并为后续的优化提供指导。Experimental techniques,as a scientific testing method,can help researchers analyze various performance indicators of the system in depth,thereby providing a basis for system optimization.This article will explore how to use experimental techniques to test and evaluate computer system performance,mainly including experimental design,construction of testing environment,selection of testing indicators,data collection and analysis,and other aspects.Firstly,a reasonable experimental design can ensure the accuracy and reliability of test results.By simulating different workloads and practical application scenarios,the performance of the system can be evaluated under different conditions.Secondly,building a stable and testing environment that meets testing requirements is key to ensuring consistency and reproducibility of test results.The selection of testing indicators should comprehensively consider multiple factors such as the processing capacity,response time,throughput,and load balancing of the computer system.Finally,the data collection and analysis process should adopt scientific statistical methods to extract valuable information,identify potential performance bottlenecks,and provide guidance for subsequent optimization.

关 键 词:计算机系统性能 实验技术 性能测试 性能评估 

分 类 号:TP393[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象