XPS: FULL: FP: Collaborative Research: Advancing autovectorization

XPS：完整：FP：协作研究：推进自动矢量化

• 批准号: 1533926
• 负责人: Alexander Veidenbaum
• 金额: $ 33.8万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1533926&HistoricalAwards=false
• 关键词: XPS; FULL; FP; Collaborative; Research

Title: XPS:FULL:FP:Collaborative Research:Advancing autovectorizationThe goal of this project is to advance the state of the art in autovectorization. This is a technique applied by compilers to automatically transform computer programs so that they can take advantage of the vector devices found in most processors. Today, most compilers have autovectorization capabilities, but their effectiveness is limited. The intellectual merit of this project lies in its potential to advance an important and beautiful core area of computer science, compiler technology, by creating new techniques and extending our understanding of programming patterns, program analysis, and transformation techniques. Beyond computer science, the project's broader significance and importance is that its results aim at increasing the fraction of code segments that, without human intervention, make use of vector devices. The effect of this increase is the acceleration of computer programs and the reduction of the energy that they consume. Faster programs are of great importance in all application areas, but are particularly important in science and engineering where computing speed is an enabler of discoveries and better designs. The research strategy is to develop and evaluate a prototype autovectorizer based on the exploration of the space of equivalent versions of a program guided by an intelligent search engine. The space of equivalent versions is obtained with a source-to-source restructurer. A repository of codelets is planned in order to train the search engine so that it becomes capable of guiding the selection in the space of possibilities in order to identify a highly efficient version of the code.

标题：XPS：FULT：FP：协作研究：推进自动化该项目的目标是在自动化方面提高最新技术。这是一项由编译器应用的技术，可以自动转换计算机程序，以便它们可以利用大多数处理器中发现的向量设备。如今，大多数编译器具有自动化功能，但其有效性是有限的。该项目的智力优点在于它通过创建新技术并扩展我们对编程模式，程序分析和转型技术的理解来推动计算机科学技术的重要核心领域的潜力。除了计算机科学之外，该项目的更广泛的意义和重要性是，其结果旨在增加代码段的比例，而无需人工干预就可以使用矢量设备。这种增加的影响是计算机程序的加速度以及减少它们消耗的能量。 更快的程序在所有应用领域都非常重要，但是在计算速度是发现和更好设计的能力的科学和工程中尤其重要。 研究策略是根据智能搜索引擎指导的程序的等效版本的探索，开发和评估原型自动配备器。用源对源重组商获得等效版本的空间。计划了一个代码集的存储库，以训练搜索引擎，以便它能够指导可能性的选择，以确定代码的高效版本。