课题基金 / 基金详情

CAREER: Compilation Techniques for Customizing Software Libraries

CAREER: Compilation Techniques for Customizing Software Libraries
职业:定制软件库的编译技术
批准号:
9984660
负责人:
Calvin Lin
金额:
$31.48万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-03-01 至 2005-02-28

项目摘要

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中文摘要
翻译
这个项目展示了一个满足世界对软件需求的愿景:通过从大型软件组件中构建程序来提高程序员的生产力,这些组件可以提供强大的抽象,可以与其他组件无缝集成,并且可以轻松地符合不同的执行环境。已经有成千上万的软件库提供这样的组件,但大多数都远远达不到在所有平台上实现无缝效率的目标。该项目将定义并实验评估一种新的方法,用于使用特定于领域和特定于机器的编译器优化来调优库。该方法的关键是一种注释语言,它传递三种类型的信息:库语义、机器特征和关于库组件将如何组合的信息。这通过封装和利用特定于领域的信息来提高其他库技术,从而获得编程抽象的好处,而不会产生通常的效率成本。该项目将关注提高性能和可移植性的三个重要机会:将传统的标量优化扩展到库优化,优化库调用序列,以及在不同机器上定制库的方法。该方法和结果将在PLAPACK密集线性代数库、MPICH消息传递库和面向对象语言(如Java)的实验中得到验证。该项目预期的研究结果包括对编译过程中特定于领域和机器的信息的使用有更深的理解,基于这些信息的新优化,以及可用于测试这些想法的编译器和语言。正如这项研究旨在改善跨界面的信息流一样,该项目的教育部分将通过为该机构的跨学科计算与应用数学项目创建“计算机科学基础”课程,试图弥合跨学科和学生群体的界面。
英文摘要
This project presents a vision for satisfying the world's demand for software: increase programmer productivity by building programs out of large software components that can provide powerful abstractions, that can be seamlessly integrated with other components, and that can easily conform to different execution environments. Thousands of software libraries already exist to provide such components, but most fall far short of the goal of seamless efficiency on all platforms. This project will define and experimentally evaluate a new approach for tuning libraries using both domain-specific and machine-specific compiler optimizations. The key to the approach is an annotation language that conveys three types of information: library semantics, machine characteristics, and information about how library components will be composed. This advances other library techniques by encapsulating and exploiting domain-specific information to reap benefits of programming abstractions without incurring their usual efficiency costs.The project will focus on three important opportunities for improving performance and portability: the extension of conventional scalar optimizations to library optimizations, the optimization of sequences of library calls, and methods for customizing libraries on different machines. The methods and results will be validated in experiments using the PLAPACK dense linear algebra library, MPICH message-passing library, and object-oriented languages such as Java. Research results expected from this project include a deeper understanding of the use of domain- and machine-specific information in the compilation process, new optimizations based on that information, and a compiler and language that can be used in testing the ideas. Just as this research seeks to improve the flow of information across interfaces, the project's educational component will attempt to bridge interfaces across disciplines and communities of the student population by creating a "Fundamentals of Computer Science" course for the institution's interdisciplinary Computational and Applied Mathematics program.
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FoMR: Using Machine Learning to Design Next Generation Caches and Data Prefetchers
  • 批准号:
    1823546
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2018
  • 负责人:
    Calvin Lin
  • 依托单位:
CS10K: Leveraging the National UTeach Network to Strengthen and Expand Computer Science Principles Education
  • 批准号:
    1543014
  • 项目类别:
    Standard Grant
  • 资助金额:
    $99.99万
  • 财政年份:
    2015
  • 负责人:
    Calvin Lin
  • 依托单位:
Type I: Project Engage!
  • 批准号:
    1138506
  • 项目类别:
    Standard Grant
  • 资助金额:
    $99.99万
  • 财政年份:
    2011
  • 负责人:
    Calvin Lin
  • 依托单位:
BPC-DP: A Planning Grant for Establishing UTeach-CS
  • 批准号:
    0959827
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.35万
  • 财政年份:
    2010
  • 负责人:
    Calvin Lin
  • 依托单位:
海外基金