Parallel linear algebra
The most common large-scale parallel architecture for scientific computing is a distributed memory computer. When using this architecture each processor has access to data stored in its own memory, while data stored by memory associated with other processors may only be accessed by communication across a network. For reasons of computational efficiency, many parallel scientific computing algorithms are implemented by partitioning the data stored so that communication across the network between processors is minimised. This project will investigate the most appropriate partitioning for linear algebra calculations.
Prerequisite: first year linear algebra. Continuous mathematics and Numerical Solution to Differential equations would be desirable.