Software

I have experience of developing scientific software in Python, C, C++, and Fortran. Often these are small codes performing analysis of simulation outputs and/or toy calculations, but I also develop and release my own packages on GitHub. I have experience of developing codes suitable for deployment on high-performance computing facilities, including use of both shared memory (OpenMP) and distributed memory (MPI) parallelism. I also have some experience in the use of Nvidia’s CUDA platform for GPU acceleration. If you are interested in working with me on a software project, please email me!

Codes Developed

• BraWl, released open-source under the GNU Lesser General Public License (LGPL).
  • A package for performing lattice-based atomistic simulations of alloys with an internal energy given by a Bragg-Williams Hamiltonian. The package implements a range of conventional and enhanced sampling techniques, including:
    • The Metropolis-Hastings Monte Carlo algorithm.
    • The Nested Sampling algorithm, implemented in collaboration with the group of Dr Livia Bartók-Pártay (Department of Chemistry, University of Warwick).
    • Wang-Landau sampling, a parallel implementation of which is available following work conducted with Hubert Naguszewski and Prof. David Quigley (Department of Physics, University of Warwick).

Codes Used

I am familiar with several community-developed density functional theory (DFT) codes, including CASTEP, JuKKR, SPR-KKR, Hutsepot, and MARMOT. I also have experience of using the Atomic Simulation Environment (ASE) to build workflows and `drive’ codes in a more automated manner.