Abstract
We present GPUQT, a quantum transport code fully implemented on graphics processing units. Using this code, one can obtain intrinsic electronic transport properties of large systems described by a realspace tightbinding Hamiltonian together with one or more types of disorder. The DC Kubo conductivity is represented as a time integral of the velocity autocorrelation or a time derivative of the mean square displacement. Linear scaling (with respect to the total number of orbitals in the system) computation time and memory usage are achieved by using various numerical techniques, including sparse matrix–vector multiplication, random phase approximation of trace, Chebyshev expansion of quantum evolution operator, and kernel polynomial method for quantum resolution operator. We describe the inputs and outputs of GPUQT and give a few examples to demonstrate its usage, paying attention to the interpretations of the results. Program summary: Program Title: GPUQT Program Files doi: http://dx.doi.org/10.17632/xbf5kbkzx7.1 Licensing provisions: GPLv3 Programming language: CUDA Nature of problem: Obtain intrinsic electronic transport properties of large systems described by realspace tightbinding Hamiltonians. Solution method: The DC conductivity is represented as a time integral of the velocity autocorrelation (VAC) or a time derivative of the mean square displacement (MSD). The calculations achieve linear scaling (with respect to the number of orbitals in the system) computation time and memory usage by using various numerical techniques, including sparse matrix–vector multiplication, random phase approximation of trace, Chebyshev expansion of quantum evolution operator, and kernel polynomial method for quantum resolution operator. Restrictions: The number of orbitals is restricted to about 20 million due to the limited amount of device memory in current GPUs.
Original language  English 

Pages (fromto)  113120 
Journal  Computer Physics Communications 
Volume  230 
Early online date  1 Jan 2018 
DOIs  
Publication status  Published  Sept 2018 
MoE publication type  A1 Journal articlerefereed 
Keywords
 GPU acceleration
 Linearscaling
 Quantum transport
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GPUQT: An efficient linearscaling quantum transport code fully implemented on graphics processing units
Fan, Z. (Creator), Vierimaa, V. (Creator) & Harju, A. (Creator), Mendeley Data, 18 May 2018
DOI: 10.17632/xbf5kbkzx7.1, https://data.mendeley.com/datasets/xbf5kbkzx7
Dataset: Software or code