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

这个小型企业创新研究(SBIR)第一阶段项目建议使计算机能够生成用于图像处理问题的高性能软件。对于计算密集型函数，到目前为止，最常见的方法是为每个新平台进行手动优化。SpiralGen的技术有可能证明，有可能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，并最大限度地利用多核)。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)是要求最高的计算领域之一，因为它的高维性质。可以从提议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(计算机断层成像)、石油勘探和计算机视觉。该公司的技术能够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，可以更快地部署功能更强大的新平台。

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.