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

俄亥俄州的Ponnuswamy Sadayappan在信息技术研究（ITR）计划下得到化学部的支持，开发程序合成工具，以促进电子结构计算的高性能并行编程。 共同PI的包括俄亥俄州的杰拉尔德·鲍姆加特纳和拉斯·皮策、路易斯安那州的贾甘纳森·拉马努贾姆和普林斯顿的马塞尔·努伊金（后两人通过合作提案CHE-0121706和CHE-0121383）。 这个由计算机科学家和计算化学家组成的团队将开发一个张量收缩引擎，该引擎可以从以高级符号表示的输入规范中合成Fortran或C中的高效并行代码，用于许多目标架构。 该工具将免费提供给其他量子化学软件的开发人员。由于算法选择对存储器访问成本和通信开销的影响，科学应用的高性能并行程序的开发变得复杂。 目前可用的软件开发和性能建模/优化工具不能为科学代码的开发人员提供足够的支持。 这项研究将提供一种新的方法来自动合成高性能的并行程序，特别强调广泛应用于化学，物理和材料科学的电子结构代码。

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.