CSR: Small: Profiling and Optimizing Embedded Software for Soft Real-Time Behavior and Responsiveness

CSR：小：分析和优化嵌入式软件的软实时行为和响应能力

• 批准号: 1320752
• 负责人: Santosh Pande
• 金额: $ 47.77万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320752&HistoricalAwards=false
• 关键词: CSR; Small; Profiling; Optimizing; Embedded

This project aims to develop a framework for performance characterization, representation, optimization and debugging for the emerging domain of soft real time computing. Key elements include a new metric, called "variance", that characterizes the timing properties of such workloads, and a "variant characterization graph" (VCG) that represents the relationships among the variance contributing functions in a software system. The VCG is subjected to a combination of static analysis, dynamic profiling and statistical analysis. The results of these analyses are applied to the problems of debugging performance bottlenecks, and dynamic performance optimization making use of predictive methods and contextual information obtained at run time. Interactive, response-time sensitive applications such as video games, computer vision, and multi-media encoder/decoders are an important, growing class of emerging applications on mobile devices such as the smart-phones. A proliferation of powerful new devices is driving up the scale and pervasiveness of applications. The diversity of new devices and the number of kinds of resources present in them, accompanied by a market-driven demand for shorter application development cycles, are making performance tuning more challenging and more essential. Success of this project would provide a practical conceptual backbone for converting the optimization of such soft real time systems from an art to a science. Transition of the results of this research to practice is furthered through open source distribution of software tools implementing and applying the VCG-based analyses, and an on-line graduate course titled "Optimizations for Interactive Embedded Software".

本项目旨在为新兴的软实时计算领域开发一个性能表征、表示、优化和调试框架。关键元素包括一个新的度量，称为“方差”，它描述了这种工作负载的时间属性，以及一个“变量特征图”（VCG），它表示了软件系统中贡献功能的方差之间的关系。VCG是静态分析、动态分析和统计分析相结合的产物。这些分析的结果应用于调试性能瓶颈问题，以及利用预测方法和在运行时获得的上下文信息进行动态性能优化。交互式、响应时间敏感的应用程序，如视频游戏、计算机视觉和多媒体编码器/解码器，是智能手机等移动设备上重要的、不断增长的新兴应用程序。强大的新设备的激增正在推动应用程序的规模和普及。新设备的多样性和其中存在的各种资源，以及市场驱动的对更短应用程序开发周期的需求，使得性能调优更具挑战性和必要性。这个项目的成功将为将这种软实时系统的优化从一门艺术转化为一门科学提供一个实用的概念支柱。通过开源软件工具的分发，实现和应用基于vcg的分析，以及名为“交互式嵌入式软件优化”的在线研究生课程，进一步将这项研究的结果转化为实践。