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From source code to runtime behaviour: Software metrics help to select the computer architecture
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DOI：10.1016/j.knosys.2009.11.014.png)
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Abstract
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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 (C) 2009 Elsevier B V All rights reserved
Keywords:
Computer architecture
Data mining
Performance prediction
Source-code metrics
Control-flow graphs
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