Large-Scale Benchmark of Electronic Structure Solvers with the ELSI Infrastructure

Victor Yu (Speaker), William Dawson (Contributor), Alberto Garcia (Contributor), Ville Havu (Contributor), Hourahine, B. (Contributor), William Huhn (Contributor), Mathias Jacquelin (Contributor), Weile Jia (Contributor), Murat Keceli (Contributor), Raul Laasner (Contributor), Yingzhou Li (Contributor), Jianfeng Lu (Contributor), Lin Lin (Contributor), Jose Roman (Contributor), Alvaro Vazquez-Mayagoitia (Contributor), Chao Yang (Contributor), Volker Blum (Contributor)

Activity: Talk or presentation typesOral presentation

Description

Routine application of electronic structure theory to systems consisting of thousands of atoms is often hindered by the solution of an eigenproblem. We here present an update to the ELectronic Structure Infrastructure (ELSI), an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), forming the foundation of our effort to rigorously benchmark the performance of the solvers on equal footing. This presentation will particularly focus on a systematic set of large-scale benchmarks for multiple solvers performed with Kohn-Sham density-functional theory and density-functional tight-binding theory. Factors that strongly affect the efficiency of the solvers are identified and analyzed, including system size and dimensionality, matrix sparsity, eigenspectrum width, number of MPI processes, etc. Based on these benchmarks, we discuss our strategy to automatically select a solver for an arbitrary problem.
Period4 Mar 2019
Held atAPS March Meeting 2019
Event typeConference
LocationBoston, United States

Keywords

  • Electronic structure theory
  • density-functional theory
  • density-functional tight-binding
  • parallel computing
  • eigensolver
  • density matrix