A parallel implementation of tight-binding molecular dynamics

Abstract

We introduce an efficient and scalable parallel implementation of tight-binding molecular dynamics which employs reordering of the atoms. This implementation also exploits the sparse character of the Hamiltonian matrix. Reordering allows our algorithm to scale well on parallel machines since it asssures data locality. A sparse storage format and a stabilized parallel Lanczos eigensolver allow consideration of large problem sizes relevant to materials science. We present a showcase application to a 1000-atom silicon sample.