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Machine Learning in Compiler Optimization
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DOI：10.1109/JPROC.2018.2817118.png)
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摘要
En 中文
In the last decade, machine-learning-based compilation has moved from an obscure research niche to a mainstream activity. In this paper, we describe the relationship between machine learning and compiler optimization and introduce the main concepts of features, models, training, and deployment. We then provide a comprehensive survey and provide a road map for the wide variety of different research areas. We conclude with a discussion on open issues in the area and potential research directions. This paper provides both an accessible introduction to the fast moving area of machine-learning-based compilation and a detailed bibliography of its main achievements.
Keyword:
Code optimization
compiler
machine learning
program tuning
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25.9
论文数:
9.9K
被引数:
4.5W
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