试点:了解如何以正确的方式进行性能基准测试的框架

Yan Li, Yash Gupta, E. L. Miller, D. Long
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引用次数: 6

摘要

执行即使是最简单的性能基准测试也需要相当多的统计学和计算机系统知识,并且需要费力地遵循许多容易出错的步骤,这些是不同的技能集,但对于获得统计上有效的结果是必不可少的。因此,同行评议出版物中的许多绩效评估都存在缺陷。在许多问题中,它们不符合以下一个或多个要求:准确性、精密度、可比性、可重复性和开销控制。这是一个严重的问题,因为糟糕的性能测量会误导系统设计和优化。我们提出了一组算法和启发式来自动化这些步骤。它们涵盖了性能度量的收集、存储、分析和比较。我们将这些方法实现为一个易于使用的开源软件框架Pilot,它可以帮助减少人为错误并缩短基准测试时间。在各种基准测试上的评估表明,它可以降低运行基准测试的成本和复杂性,并且可以产生更好的测量结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pilot: A Framework that Understands How to Do Performance Benchmarks the Right Way
Carrying out even the simplest performance benchmark requires considerable knowledge of statistics and computer systems, and painstakingly following many error-prone steps, which are distinct skill sets yet essential for getting statistically valid results. As a result, many performance measurements in peer-reviewed publications are flawed. Among many problems, they fall short in one or more of the following requirements: accuracy, precision, comparability, repeatability, and control of overhead. This is a serious problem because poor performance measurements misguide system design and optimization. We propose a collection of algorithms and heuristics to automate these steps. They cover the collection, storing, analysis, and comparison of performance measurements. We implement these methods as a readily-usable open source software framework called Pilot, which can help to reduce human error and shorten benchmark time. Evaluation of Pilot on various benchmarks show that it can reduce the cost and complexity of running benchmarks, and can produce better measurement results.
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