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Small: Collaborative Research: Transform-to-Perform: Languages, Algorithms, and Code Transformations for High-Performance FEM

Small: Collaborative Research: Transform-to-Perform: Languages, Algorithms, and Code Transformations for High-Performance FEM
小:协作研究:从转换到执行:高性能 FEM 的语言、算法和代码转换
批准号:
1524433
负责人:
Andreas Kloeckner
金额:
$21.94万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-15 至 2019-06-30

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中文摘要
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英文摘要
Simulation of natural and engineering phenomena is a multi-layered technical task with high demands on mathematical sophistication and computational power. Producing a computer simulation code requires work at many different levels of detail. A computer program should represent a scientific problem in a language close to that used by domain specialists, but this differs greatly from low-level, hardware-specific details of computers. Bridging between the two requires several different links. This project sets up many intermediate software stages, called ?representations? modeling the domain knowledge of engineers, numerical analysts, and computer scientists by describing partial differential equations, the so-called weak forms needed for numerical methods, loop nests required to build discrete operations, and finally low-level code that can be executed by computers. ?Transformations? are then programs connecting these representations, injecting knowledge about algorithms and hardware. The key advance in this research is that, through this chain of transformations, domain knowledge about each level of detail, be it application-related, numerical, or computational, can be supplied at the appropriate level of detail. The tools developed in this project promote the advancement of science by both shortening the development time and increasing the resulting power of high-performance simulation codes used by scientists and engineers, enabling them to impact the world.
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SHF: Small: Collaborative Research: Transform-to-Perform: Languages, Algorithms, and Solvers for Nonlocal Operators
Elements: Transformation-Based High-Performance Computing in Dynamic Languages
CAREER: Towards General-Purpose, High-Order Integral Equation Methods for Computer Simulation in Engineering: Analysis, Algorithm Design, and Applications
Collaborative Research: Efficient High-Order Parallel Algorithms for Large-Scale Photonics Simulation
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