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From source code to runtime behaviour: Software metrics help to select the computer architecture

机译:从源代码到运行时行为:软件指标有助于选择计算机体系结构

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摘要

The decision which hardware platform to use for a certain application is an important problem in computer architecture. This paper reports on a study where a data-mining approach is used for this decision. It relies purely on source-code characteristics, to avoid potentially expensive programme executions. One challenge in this context is that one cannot infer how often functions that are part of the application are typically executed. The main insight of this study is twofold: (a) Source-code characteristics are sufficient nevertheless, (b) Linking individual functions with the runtime behaviour of the programme as a whole yields good predictions. In other words, while individual data objects from the training set may be quite inaccurate, the resulting model is not.
机译:决定为某个应用程序使用哪个硬件平台是计算机体系结构中的重要问题。本文报告了一项研究,其中将数据挖掘方法用于此决策。它纯粹依赖于源代码特性,以避免潜在的昂贵程序执行。在这种情况下的一个挑战是,人们无法推断出作为应用程序一部分的功能通常被执行的频率。这项研究的主要见解有两个方面:(a)尽管如此,源代码特性还是足够的;(b)将单个函数与程序的运行时行为链接在一起,可以产生良好的预测。换句话说,虽然训练集中的单个数据对象可能非常不准确,但所得模型却并非如此。

著录项

  • 来源
    《Knowledge-Based Systems》 |2010年第4期|p.343-349|共7页
  • 作者单位

    Institute for Programme Structures and Data Organisation (IPD), Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany;

    Institute for Computer Science and Engineering (ITEC), Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany;

    Institute for Programme Structures and Data Organisation (IPD), Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany;

    Institute for Computer Science and Engineering (ITEC), Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    computer architecture; data mining; performance prediction; source-code metrics; control-flow graphs;

    机译:计算机架构;数据挖掘;性能预测;源代码指标;控制流图;

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