A CUDA implementation of a linear-scaling quantum transport method. This code can be used to obtain intrinsic electronic transport properties of large systems described by a real-space tight-binding Hamiltonian together with one or more types of disorder.

The major reference for the CUDA implementation is

• Z. Fan, A. Uppstu, T. Siro, and A. Harju, Efficient linear-scaling quantum transport calculations on graphics processing units and applications on electron transport in graphene, Comput. Phys. Commun. 185, 28 (2014).

• After downloading and unpacking GPUQT, one can see two folders: "src" and "examples".

• The folder "src" contains all the source files (with suffix .h or .cu) of the main code and a makefile. The source files are:

  • main.cu - the main function
  • common.h - some constants
  • gpuqt.h and gpuqt.cu - the "driver function"
  • sigma.h and sigma.cu - functions to obtain the transport properties
  • model.h and model.cu - class to define the simulation model
  • hamiltonian.h and hamiltonian.cu - class to perform the matrix-related operations
  • vector.h and vector.cu - class to perform the vector-related operations

• The folder "examples" contains two sub-folders with names "diffusive" and "localized", both containing the files "make_inputs.cpp" and "plot_results.m".

• There is also a file named "input.txt" in the "examples" folder, which is a "driver input file".

Need a computer/workstation/cluster equipped with one or more CUDA-enabled GPUs with compute capability of 2.0 or higher, a g++ compiler and a CUDA toolkit. The code has only been tested in linux systems.

Go to "src" and type "make" to compile the gpuqt code. This will produce an executable "gpuqt" in the "src" folder.

• Go to the folders "diffusive" and "localized", compile the C++ codes with the "-std=c++11" option, and run the executables. This will produce all the input files (with suffix .in) for the examples.

• Go to the main folder where you can see the "src" folder and type "src/gpuqt examples/input.txt" to run the examples. The data will be written into the output files (with suffix .out) in the "diffusive" and "localized" folders. If you run a simulation multiple times, new data will be appended to the existing output files.

Go to the folders "diffusive" and "localized" and run the MATLAB scripts. You should get similar figures as in the following paper:

• Z. Fan, V. Vierimaa, and Ari Harju, GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units, arXiv:1705.01387 [physics.comp-ph], submitted to Comput. Phys. Commun. on May 3, 2017.

• Zheyong Fan (Aalto University): Wrote the first working version of this code.

• Ville Vierimaa (Aalto University): Changed the code from the original C style to the current C++ style and made many other improvements.

• Ari Harju (Aalto University): The supervisor of this project.

• Zheyong Fan: brucenju(at)gmail.com; zheyong.fan(at)aalto.fi; zheyongfan(at)163.com