SBIR Phase I: Computer Generation and Optimization of Image Processing Functions

SBIR 第一阶段：图像处理功能的计算机生成和优化

• 批准号: 1013936
• 负责人: Yevgen Voronenko
• 金额: $ 15万
• 依托单位: SpiralGen Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1013936&HistoricalAwards=false
• 关键词: SBIR; Phase; Computer; Generation; Optimization

This Small Business Innovation Research (SBIR) Phase I project proposes to enable computer generation of high performance software for image processing problems. For computing intensive functions, the by far most common approach is hand-optimization for every new platform. SpiralGen's technology has the potential to demonstrate that it is possible to automatically produce performance-competitive code (code that is a good as human-written code and takes optimal advantage of multiple cores) for an important class of image processing functions. The approach is based on a blend of mathematics, programming languages, symbolic computation, compilers, and optimization. Image processing (including its close cousin video processing) is one of the most demanding computing domains due to its higher-dimensional nature. Key application domains that can benefit from the proposed technology include military applications (surveillance, target recognition), consumer multimedia processing, medical imaging (computer tomography), oil exploration, and computer vision. The company's technology has the ability to provide a longterm solution to the porting and optimization problem: applications are ported by regenerating performance critical components optimized for the new platform. As a result, new more capable platforms can be deployed faster.

这个小企业创新研究（SBIR）第一阶段项目提出，使计算机生成的高性能软件的图像处理问题。对于计算密集型功能，到目前为止最常见的方法是针对每个新平台进行手动优化。 SpiralGen的技术有可能证明，可以为一类重要的图像处理功能自动生成具有性能竞争力的代码（与人类编写的代码一样好的代码，并充分利用多个核心）。 该方法基于数学、编程语言、符号计算、编译器和优化的混合。图像处理（包括其近亲视频处理）是由于其高维性质而要求最高的计算领域之一。 可以从所提出的技术中受益的关键应用领域包括军事应用（监视，目标识别），消费者多媒体处理，医学成像（计算机断层扫描），石油勘探和计算机视觉。 该公司的技术有能力为移植和优化问题提供长期解决方案：通过重新生成针对新平台优化的性能关键组件来移植应用程序。因此，可以更快地部署新的功能更强大的平台。