NGS: Collaborative: Continuous Compilation: A New Approach to Aggressive and Adaptive Code Transformation

NGS：协作：持续编译：积极和自适应代码转换的新方法

• 批准号: 0203945
• 负责人: Mary Lou Soffa
• 金额: $ 15.98万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0203945&HistoricalAwards=false
• 关键词: NGS; Collaborative; Continuous; Compilation; New

Title: Collaborative Research: Continuous Compilation: A New Approach to Aggressive and Adaptive Code Transformation Today's challenge for optimization research is to develop new techniques and approaches that yeild performance improvements that were typical of early optimization research-20 to 40 percent and more. In this research, we address this challenge by investigation and developing an innobative system or applying optimizations. Our system, the Continuous Compilation System (COCO), applies optimizations both statically at compile-time and dynamically at run-time using optimization plans developed at compile time and adapted at run time. To demonstrate the practicality and utility of our approach, initially we will apply COCO to several large, long-running applications. Examples of such applications include ecological simulations, weather simulation, architecture simulators, and VLSI routing and placement applications. As we gain insight and experience with the application of continuous compilation, we will investigate its effectiveness on other types of codes such as multimedia applications, signal processing applications, and web servers.

标题：协作研究：连续汇编：一种积极和适应性代码转型的新方法，当今对优化研究的挑战是开发新技术和方法，使得Yeild绩效改进是早期优化研究-20至40％及以上的典型特征。 在这项研究中，我们通过调查和开发一个无知的系统或应用优化来应对这一挑战。我们的系统是连续编译系统（COCO），使用在编译时制定并在运行时进行调整的优化计划在运行时静态地进行优化。 为了证明我们方法的实用性和实用性，最初，我们将将可可应用于几个大型长期运行的应用程序。此类应用程序的示例包括生态模拟，天气模拟，架构模拟器以及VLSI路由和放置应用程序。随着我们在连续汇编的应用中获得洞察力和经验，我们将研究其在其他类型的代码（例如多媒体应用程序，信号处理应用程序和Web服务器）上的有效性。