Computation of particle interactions in n-dimensional space
"Aboria (https://github.com/martinjrobins/Aboria) is a C++ library for evaluating and solving systems of equations that can be described as interactions between particles in n-dimensional space. It can be used as a high performance library to implement numerical methods such as Molecular Dynamics in computational chemistry, or Gaussian Processes for machine learning.
Project 1: Aboria features a radial neighbour search to find nearby particles in the n-dimensional space, in order to calculate their interactions. This project will implement a new algorithm based on calculating the interactions between neighbouring *clusters* of particles. Its performance will be compared against the existing implementation, and across the different spatial data structures used by Aboria (Cell-list, Octree, Kdtree). Prerequisites: C++
Project 2: Aboria features a serial Fast Multipole Algorithm (FMM) for evaluating smooth long range interactions between particles. This project will implement and profile a parallel FMM algorithm using CUDA and/or the Thrust library.
Prerequisites: C++, Knowledge of GPU programming using CUDA and/or Thrust
Project 3: The main bottleneck of the FMM is the interactions between well-separated particle clusters, which can be described as low-rank matrix operations. This project will explore different methods compressing these matrices in order to improve performance, using either Singular Value Decomposition (SVD), Randomised" SVD, or Adaptive Cross Approximation
Prerequisites: C++, Linear Algebra