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

俄亥俄州立大学的 Ponnuswamy Sadayappan 在信息技术研究 (ITR) 计划下的化学部门的支持下开发程序综合工具，以促进电子结构计算的高性能并行编程。 联合 PI 包括俄亥俄州立大学的 Gerald Baumgartner 和 Russ Pitzer、路易斯安那州立大学的 Jagannathan Ramanujam 和普林斯顿大学的 Marcel Nooijen（后两者来自合作提案 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种张量收缩引擎，该引擎可以根据以高级符号表示的输入规范，针对多种目标架构合成 Fortran 或 C 语言中的高效并行代码。 该工具将免费提供给量子化学软件的其他开发人员。由于算法选择对内存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。 当前可用的软件开发和性能建模/优化工具没有为科学代码开发人员提供足够的支持。 这项研究将为高性能并行程序的自动合成提供一种新颖的方法，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.