Linear scaling algorithms: Progress and promise
The goal of this laboratory-directed research and development (LDRD) project was to develop a new and efficient electronic structure algorithm that would scale linearly with system size. Since the start of the program this field has received much attention in the literature as well as in terms of focused symposia and at least one dedicated international workshop. The major success of this program is the development of a unique algorithm for minimization of the density functional energy which replaces the diagonalization of the Kohn-Sham hamiltonian with block diagonalization into explicit occupied and partially occupied (in metals) subspaces and an implicit unoccupied subspace. The progress reported here represents an important step toward the simultaneous goals of linear scaling, controlled accuracy, efficiency and transferability. The method is specifically designed to deal with localized, non-orthogonal basis sets to maximize transferability and state by state iteration to minimize any charge-sloshing instabilities and accelerate convergence. The computational demands of the algorithm do scale as the particle number, permitting applications to problems involving many inequivalent atoms. Our targeted goal is at least 10,000 inequivalent atoms on a teraflop computer. This report describes our algorithm, some proof-of-principle examples and a state of the field at the conclusion of this LDRD.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 285454
- Report Number(s):
- SAND--96-2060; ON: DE96014410
- Country of Publication:
- United States
- Language:
- English
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