ITR/AP:Collaborative Research - Synthesis of High Performance Algorithms for Electronic

ITR/AP：合作研究 - 电子高性能算法综合

基本信息

批准号：
0450462
负责人：
So Hirata
金额：
$ 24.09万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2004
资助国家：
美国
起止时间：
2004-06-22 至 2006-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0450462&HistoricalAwards=false
关键词：
ITR AP Collaborative Research Synthesis

项目摘要

Ponnuswamy Sadayappan of Ohio State is supported by the Chemistry Division under the Information Technology Research (ITR) program to develop program synthesis tools that will facilitate high-performance parallel programming for electronic structure calculations. Co-PI's include Gerald Baumgartner and Russ Pitzer of Ohio State, Jagannathan Ramanujam of Louisiana State, and Marcel Nooijen of Princeton, (the latter two via collaborative proposals CHE-0121706 and CHE-0121383). This team of computer scientists and computational chemists will develop a tensor contraction engine that can synthesize efficient parallel code in Fortran or C from an input specification expressed in a high-level notation, for a number of target architectures. This tool will be made freely available to other developers of quantum chemistry software.The development of high-performance parallel programs for scientific applications is complicated by the effects of algorithm choice on memory access costs and communication overhead. Currently available tools for software development and performance modeling/optimization do not provide adequate support to developers of scientific code. This research will provide a novel approach to the automated synthesis of high-performance parallel programs, with the particular emphasis on electronic structure codes widely employed in chemistry, physics, and materials science.

俄亥俄州立大学的Ponnuswamy Sadayappan得到了信息技术研究（ITR）计划的化学部门的支持，以开发计划合成工具，这些工具将有助于电子结构计算的高性能并行编程。 Co-Pi包括俄亥俄州立大学的Gerald Baumgartner和Russ Pitzer，路易斯安那州的Jagannathan Ramanujam和Princeton的Marcel Nooijen（后两个通过协作提案CHE-0121706和CHE-0121383）。该计算机科学家和计算化学家团队将开发张量的收缩引擎，该引擎可以从高级符号中表达的输入规范中综合有效的Fortran或C中的有效并行代码，以提供许多目标架构。该工具将免费提供给其他量子化学软件的开发商。对于科学应用程序，高性能并行程序的开发使算法选择对内存访问成本和交流开销的影响变得复杂。当前可用于软件开发和性能建模/优化的工具不能为科学代码的开发人员提供足够的支持。这项研究将为高性能平行程序的自动合成提供一种新颖的方法，并特别强调了广泛用于化学，物理学和材料科学的电子结构代码。