Automatic Derivation of Code Generators from Machine Descriptions

Author:

Cattell R. G.1

Affiliation:

1. Xerox Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA

Abstract

Work with compiler compilers has dealt principally with automatic generation of parsers and lexical analyzers. Until recently, little work has been done on formalizing and generating the back end of a compiler, particularly an optimizing compiler. This paper describes formalizations of machines and code generators and describes a scheme for the automatic derivation of code generators from machine descriptions. It was possible to separate all machine dependence from the code generation algorithms for a wide range of typical architectures (IBM-360, PDP-11, PDP-10, Intel 8080) while retaining good code quality. Heuristic search methods from work in artificial intelligence were found to be both fast and general enough for use in generation of code generators with the machine representation proposed. A scheme is proposed to perform as much analysis as possible at code generator generation time, resulting in a fast pattern-matching code generator. The algorithms and representations were implemented to test their practicality in use.

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Reference27 articles.

1. ALLEN F. CARTER J. HARRISON W. LOEWNER P. TAPSCOTT R. TREVILLYAN L. AND WECMAN M. The experimental compiling systems project. IBM Res. Rep. RC 6718 (#28922) IBM Yorktown Heights N. Y. 1977. ALLEN F. CARTER J. HARRISON W. LOEWNER P. TAPSCOTT R. TREVILLYAN L. AND WECMAN M. The experimental compiling systems project. IBM Res. Rep. RC 6718 (#28922) IBM Yorktown Heights N. Y. 1977.

Cited by 64 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Lightweight, Modular Verification for WebAssembly-to-Native Instruction Selection;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1;2024-04-17

2. Unveiling the Potential of Large Language Models in Generating Semantic and Cross-Language Clones;2023 IEEE 17th International Workshop on Software Clones (IWSC);2023-10-01

3. Bibliography;Engineering a Compiler;2023

4. Instruction Selection;Engineering a Compiler;2023

5. VeGen: a vectorizer generator for SIMD and beyond;Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems;2021-04-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3