Abstract
This paper describes an efficient sparse linear solver for block tri-diagonal systems arising from atomistic device simulation based on the nearest-neighbor tight-binding method. The algorithms a parallel Gaussian elimination of blocks corresponding to atomic layers instead of single elements. It is known in the physics community as the renormalization method introduced in 1989 by Grosso et al, (Phys. Rev. B. 40 12328 (1989)]. Here we describe in details the functionality of the algorithm and we show that it is faster than direct sparse linear packages like MUMPS or SuperLu_DIST and that it scales well up to 512 processors.;
Date of this Version
August 2008
Recommended Citation
Luisier, Mathieu; Fichtner, Wolfgang; Schenk, Andreas; Boykin, Timothy B.; and Klimeck, Gerhard, "A parallel sparse linear solver for nearest-neighbor tight-binding problems" (2008). Other Nanotechnology Publications. Paper 145.
https://docs.lib.purdue.edu/nanodocs/145
Comments
14th International Conference on parallel and Distributed Computing, Aug. 26-29, Las Palmas de Gran Canaria Spain, 89 accepted papers out of 264 submissions.