AUTOMATIC CODE GENERATION OF HIGH PERFORMANCE FOURIER TRANSFORM LIBRARIES

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 本研究的目标是在超级计算机平台上实现离散傅立叶变换（DFT）库的自动代码生成和优化。用于各种平台的DFT（及其变体）的大多数当前高性能并行实现通常是手动编码和手动调整的，以用于单个变换/大小，并且被约束到特定的数据格式。我们的目标是自动化生成高性能DFT库的过程，用于超级计算平台的各种问题规范和场景。我们的方法使用算法操作在一个高层次的抽象，基于一组数学规则，这使得自动化的库生成。傅立叶变换是一种计算内核，广泛用于科学计算，包括生物医学图像处理。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The objective of this research is the automatic code generation and optimization of discrete Fourier transform (DFT) libraries for supercomputer platforms. Most current high performance parallel implementations of the DFT (and its variants) for various platforms are typically hand-coded and manually tuned to work for a single transform/size, and are constrained to specific data formats. Our goal is to automate the process of generating high-performance DFT libraries for a wide variety of problem specifications and scenarios for supercomputing platforms. Our approach uses algorithmic manipulation at a high level of abstraction, based on a set of mathematical rules, which allows automation of library generation. The Fourier transform is a compute kernel that is used extensively in scientific computing, including biomedical image processing.