ITR: Building Practical Compilers Based on Adaptive Search

ITR：基于自适应搜索构建实用编译器

• 批准号: 0205303
• 负责人: Keith Cooper
• 金额: $ 160万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2008-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205303&HistoricalAwards=false
• 关键词: ITR; Building; Practical; Compilers; Based

The information age is built on software. Web browsers and servers, office productivity tools, anti-lock brake systems, cellular telephones, and online trading systems are all implemented in software. Most of that code is prepared for execution using a compiler.For four decades, compilers have applied a fixed sequence of transformations to the code. The fact that different transformations, applied in different orders, can produce different results has been known, but the techniques for picking effective transformation sequences have not. The computational power available with modern processors makes it possible to experimentally discover good transformation orders.This project will systematically explore the problems of choosing transformation sequences. This five-year program will develop practical techniques for building adaptive compilers - compilers that change their behavior in response to the input program and the end-user's stated goals for optimization. This will require experimentation, algorithm development, application of techniques from machine learning, and basic software engineering. This project will produce the tools, techniques, and insights needed to make adaptive compilation both practical and productive. The resulting compilers will give users greater control over the run-time characteristics of their programs and will reduce the performance variability that plagues compiled code today.

信息时代是建立在软件之上的。 Web浏览器和服务器、办公生产力工具、防抱死制动系统、移动电话和在线交易系统都是用软件实现的。 大多数代码都是使用编译器准备执行的，四十年来，编译器一直对代码应用固定的转换序列。 以不同顺序应用的不同变换可以产生不同的结果，这一事实是已知的，但是用于挑选有效变换序列的技术还没有。现代处理器的计算能力使得通过实验发现好的变换顺序成为可能。本项目将系统地探讨选择变换顺序的问题。这个为期五年的计划将开发用于构建自适应编译器的实用技术-编译器根据输入程序和最终用户的优化目标改变其行为。这将需要实验、算法开发、机器学习技术的应用以及基本的软件工程。该项目将产生使自适应编译既实用又高效所需的工具、技术和见解。由此产生的编译器将使用户能够更好地控制其程序的运行时特性，并将减少困扰当今编译代码的性能可变性。