Computation of electron quantum transport in graphene nanoribbons using GPU

TL;DR

This paper demonstrates that GPUs significantly accelerate quantum electron transport simulations in graphene nanoribbons, though numerical errors can occur near the charge neutrality point due to single-precision calculations.

Contribution

It presents an implementation of the recursive Green's function algorithm on GPUs for graphene nanoribbons, highlighting performance gains and numerical challenges.

Findings

GPUs offer substantial speed-ups over CPUs for large graphene ribbons.

Single-precision arithmetic introduces notable numerical errors near the charge neutrality point.

Implementation details facilitate future GPU-based quantum transport simulations.

Abstract

The performance potential for simulating quantum electron transport on graphical processing units (GPUs) is studied. Using graphene ribbons of realistic sizes as an example it is shown that GPUs provide significant speed-ups in comparison to central processing units as the transverse dimension of the ribbon grows. The recursive Green's function algorithm is employed and implementation details on GPUs are discussed. Calculated conductances were found to accumulate significant numerical error due to single-precision floating-point arithmetic at energies close to the charge neutrality point of the graphene.