U.S.-Germany Cooperative Research: High-Performance Execution of Nested Data Parallelism in Fortran Programs

该奖项支持Jan Prins博士，Siddhartha Chatterjee的联合pi，以及北卡罗莱纳大学教堂山分校的研究生与柏林工业大学通信与软件工程系的Stefan J -ª- hnichen合作。此次合作将研究高性能计算，目的是将嵌套并行性集成到高性能Fortran （HPF）和Fortran 95编程语言中。（HPF是Fortran 95的一个变体，专门用于以一种不依赖于计算机体系结构的方式编写高性能并行计算机。）现在正是将这项新技术整合到Fortran中的时候，这样应用程序就可以在不中断正在进行的开发的情况下利用该功能。嵌套并行性使自适应和稀疏解决方案技术的表达成为可能，这些技术是执行日益庞大和精确的科学计算所必需的。这项合作结合了两个研究小组的互补优势和设施。

This award supports Dr. Jan Prins, co-PI Siddhartha Chatterjee, and a graduate student from the University of North Carolina-Chapel Hill in a collaboration with Stefan Jªhnichen of the Department of Communications and Software Engineering at the Technical University of Berlin. The collaboration will study high-performance computing with the aim of integrating nested parallelism into the High Performance Fortran (HPF) and Fortran 95 programming languages. (HPF is a variant of Fortran 95 specifically targeted for programming high-performance parallel computers in a way that does not depend on the computer architecture.) The time is right to incorporate this new technology into Fortran so that applications can take advantage of the capability without disrupting ongoing development. Nested parallelism enables the expression of adaptive and sparse solution techniques necessary to performing increasingly large and precise scientific computations. The collaboration combines the complementary strengths and facilities of the two research groups.