ELSI: A unified software interface for Kohn–Sham electronic structure solvers
- Duke Univ., Durham, NC (United States). Dept. of Mechanical Engineering
- Imperial College, London (United Kingdom). Depts. of Materials and Physics
- Institut de Ciència de Materials de Barcelona, Bellaterra (Spain)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Univ. of California, Berkeley, CA (United States). Dept. of Mathematics
- Duke Univ., Durham, NC (United States). Dept. of Mathematics
- Argonne National Lab. (ANL), Argonne, IL (United States). Leadership Computing Facility
Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn-Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn-Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn-Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. As a result, comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); Argonne National Laboratory, Argonne Leadership Computing Facility; National Science Foundation (NSF); USDOE Office of Science (SC), National Energy Research Scientific Computing Center (NERSC); Spanish Ministerio de Economia y Competitividad (MINECO)
- Grant/Contract Number:
- AC02-05CH11231; AC02-06CH11357
- OSTI ID:
- 1525279
- Alternate ID(s):
- OSTI ID: 1421968; OSTI ID: 1495536
- Journal Information:
- Computer Physics Communications, Vol. 222, Issue C; ISSN 0010-4655
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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