Collaborative Research: SI2-SSI: ELSI-Infrastructure for Scalable Electronic Structure Theory

预测性的，所谓从头开始的电子结构计算，特别是基于Kohn-Sham密度泛函理论（DFT）的电子结构计算，现在已经广泛应用于几乎所有科学领域，并且越来越多地应用于工程和工业领域。在材料科学领域，它们使性能改进的新材料的计算（“计算机”）设计成为可能。在生物学或药理学研究中，它们为大分子或药物的功能提供分子水平的见解。在寻找新能源解决方案的过程中，他们为新的太阳能电池设计、催化过程和许多其他方面提供了分子水平的见解。许多应用程序和计算中的一个关键瓶颈是所谓的Kohn-Sham特征值问题的“立方缩放墙”，该问题与系统大小有关（即，如果模型大小增加10倍，则工作量增加1000倍）。该项目将建立一个开源软件基础设施“ELSI”，为最初的三个互补解决方案策略提供一个通用的、实用的接口，以减轻或克服与解决Kohn-Sham特征值问题相关的困难。ELSI将支持广泛的最终用户社区，以不同的代码为中心，通常具有独特的功能，将专门的科学家小组与特定的解决方案联系起来，轻松地将最先进的解决方案策略整合到他们共享的关键问题中。通过提供这些有效的、可访问的解决方案策略，我们将为基于DFT的预测方法目前不适用的电子结构理论开辟主要领域。这将反过来为材料科学、化学和所有相关领域的新发展打开大门。支持ELSI的承诺来自一些最重要的电子结构开发人员社区，以及高性能计算领域的行业和政府领导者。因此，我们将创建一个强大的基于美国的基础设施，利用来自全球活跃社区的大型用户和开发人员基础，开发用于材料研究的DFT方法。ELSI将支持和增强三种最先进的方法，每种方法最适合特定的问题范围：(i) ELPA （EigensoLvers for Petascale Applications）库，这是一个领先的库，用于高效、大规模并行解决特征值问题（用于多达1000个原子的中小型问题），（ii） OMM（轨道最小化方法）在最近的重新实现中，通过专注于简化的辅助问题（用于数千个原子范围的系统）来绕过特征值问题，以及（iii） PEXSI（极点扩展和选择性反演）库。一般系统（用于具有1000个原子及以上的问题）的已证明的减少缩放（最多二次缩放）解决方案。通过以许多电子结构开发人员已经熟悉的风格建立标准化接口，ELSI将使使用它的生产电子结构代码能够显着减少特征值问题的“缩放墙”。首先，ELSI将帮助他们有效地利用最强大的计算平台。目标平台是当前的大规模并行计算机和多核架构，基于GPU的系统和未来的多核处理器。其次，该项目将对ELPA、OMM和PEXSI进行有针对性的方法改进，例如，对非常大的系统更有效地使用矩阵稀疏性。对类似的计算架构和类似的方法增强的关注将导致这些方法之间的重要交叉受精和协同作用。

Predictive, so-called ab initio electronic structure calculations, particularly those based on the Kohn-Sham density functional theory (DFT) are now a widely used scientific workhorse with applications in virtually all sciences, and increasingly in engineering and industry. In materials science, they enable the computational ("in silico") design of new materials with improved properties. In biological or pharmacological research, they provide molecular-level insights into the function of macromolecules or drugs. In the search for new energy solutions, they give molecular-level insights into new solar cell designs, catalytic processes, and many others. A key bottleneck in many applications and calculations is the "cubic scaling wall" of the so-called Kohn-Sham eigenvalue problem with system size (i.e., the effort increases by a factor of 1,000 if the model size increases by a factor of 10). This project will establish an open source software infrastructure "ELSI" that offers a common, practical interface to initially three complementary solution strategies to alleviate or overcome the difficulty associated with solving the Kohn-Sham eigenvalue problem. ELSI will enable a broad range of end user communities, centered around different codes with, often, unique features that tie a specialized group of scientists to that particular solution, to easily incorporate state-of-the-art solution strategies for a key problem they all share. By providing these effective, accessible solution strategies, we will open up major areas for electronic structure theory where DFT based predictive methodologies are not applicable today. This will in turn open doors for new development in materials science, chemistry, and all related areas. Commitments to support ELSI exist from some of the most important electronic structure developer communities, as well as from industry and government leaders in high-performance computing. Thus, we will create a strong U.S. based infrastructure that leverages the large user and developer base from a globally active community developing DFT methods for materials research.ELSI will support and enhance three state-of-the-art approaches, each best suited for a specific problem range: (i) The ELPA (EigensoLvers for Petascale Applications) library, a leading library for efficient, massively parallel solution of eigenvalue problems (for small- and mid-sized problems up to several 1,000s of atoms), (ii) the OMM (Orbital Minimization Method) in a recent re-implementation, which circumvents the eigenvalue problem by focusing on a reduced, auxiliary problem (for systems in the several 1,000s of atoms range), and (iii) the PEXSI (Pole EXpansion and Selective Inversion) library, a proven reduced scaling (at most quadratic scaling) solution for general systems (for problems with 1,000s of atoms and beyond). By establishing standardized interfaces in a style already familiar to many electronic structure developers, ELSI will enable production electronic structure codes that use it to significantly reduce the "scaling wall" of the eigenvalue problem. First, ELSI will help them make efficient use of the most powerful computational platforms available. The target platforms are current massively parallel computers and multicore architectures, GPU based systems and future manycore processors. Second, the project will make targeted methodological improvements to ELPA, OMM, and PEXSI, e.g., a more effective use of matrix sparsity towards very large systems. The focus on similar computational architectures and similar methodological enhancements will lead to significant cross-fertilization and synergy between these approaches.