Projects
The Centre for Parallel Computing has a number of research projects that investigate how parallel computing can be used to accelerate the scientific process. These projects aim to develop efficient implementations of scientific simulations and algorithms for the parallel devices at Massey University. The following are some brief descriptions of the simulations being investigated by the members of the CPC.
Name 
Description 
Members 
Publications 
NBody 
Nbody simulations approximate the motion of a system of particles  often with some potential between them. These simulations can range in scale from interacting particles to stars and galaxies. Simulations may use a variety of numerical methods to approximate the particles' motion, they may also include collision detection/response models. The Nbody project investigates the development of parallel implementations of Nbody simulations. Efforts have been directed towards developing GPU and mGPU implementations of these simulations and investigating the associated challenges. Features investigated include:



Field Equations 
Field equation models approximate the behaviour of a field as determined by a governing equation. The field is usually approximated by a discrete grid and the spatial terms of the equations by discrete stencils. Specific field equations investigated include: CahnHilliard, LotkaVolterra, GinzburgLandau and Heisenberg. This project explores methods of implementing field equation simulations on parallel devices including GPUs, mGPU systems, GPUclusters, Cell Broadband Engines and multicore machines.


CSTN065 
Network Generation/Analysis 
Complex Networks such as scalefree networks or smallworld networks are necessary to model many systems in mathematics, physics, biology and computer science. Simulations using these networks can exhibit behaviour that is simply not seen on regular or random data structures. However, for large systems the generation and analysis of these networks presents a significant computational challenge. This project aims to investigate and develop efficient parallel algorithms and data storage patterns for use with these network structures. Features investigated include:



Latticebased Computational Models 
Latticebased computational models often show complex behaviour emerging from simple set of state and rules. The behaviour of these models can often mimic or approximate the behaviour of complex equations. Models investigated include: Lattice Gas, Ising, Potts, Sznajd and Game of Life. This project investigates how these latticebased computational models can be efficiently implemented on parallel devices. Features investigated include:


CSTN093 
Scientific Visualisation 
Visualisation is an important component of most scientific simulations. Correct visualisation of a simulation allows the behaviour of the simulation to be observed and are vital in identifying many important phenomena. Advanced visualisation methods often require a lot of preprocessing and data analysis to generate the visualisation. Parallel computing techniques can be used to perform this preprocessing in real time and allow the observer to interact with the simulation in realtime. Techniques Include:

