A projected preconditioned conjugate gradient algorithm for computing many extreme eigenpairs of a Hermitian matrix [A projected preconditioned conjugate gradient algorithm for computing a large eigenspace of a Hermitian matrix]
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Here, we present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimal block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- Grant/Contract Number:
- AC52-07NA27344; AC02-05CH11231
- OSTI ID:
- 1325863
- Alternate ID(s):
- OSTI ID: 1556219
- Report Number(s):
- LLNL-JRNL-695289
- Journal Information:
- Journal of Computational Physics, Vol. 290, Issue C; ISSN 0021-9991
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Prediction of atomization energy using graph kernel and active learning
|
journal | January 2019 |
Convergence theory for preconditioned eigenvalue solvers in a nutshell | text | January 2014 |
Similar Records
A parallel additive Schwarz preconditioned Jacobi-Davidson algorithm for polynomial eigenvalue problems in quantum dot simulation
Computing several eigenpairs of Hermitian problems by conjugate gradient iterations