Opendda: a Novel High-Performance Computational Framework for the Discrete Dipole Approximation

This work presents a highly-optimised computational framework for the Discrete Dipole Approximation, a numerical method for calculating the optical properties associated with a target of arbitrary geometry that is widely used in atmospheric, astrophysical and industrial simulations. Core optimisations include the bit-fielding of integer data and iterative methods that complement a new Discrete Fourier Transform (DFT) kernel, which efficiently calculates the matrix-vector products required by these iterative solution schemes. The new kernel performs the requisite 3D DFTs as ensembles of 1D transforms, and by doing so, is able to reduce the number of constituent 1D transforms by 60% and the memory by over 80%. The optimisations also facilitate the use of parallel techniques to further enhance the performance. Complete OpenMP-based shared-memory and MPI-based distributed-memory implementations have been created to take full advantage of the various architectures. Several benchmarks of the new framework indicate extremely favourable performance and scalability.