CUDA Fortran

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Projects

Deep Optimisation

Jamie Caldwell

The project will develop the implementation and application of a new optimisation technique. 'Deep optimisation' combines deep learning techniques in neural networks with distributed optimisation methods to create a dynamically re-scalable optimisation process. This project will develop this technique to better-understand its capabilities and limitations and develop GPU implementations. The protein structure prediction problem will be used as the main test application.

Massively-Parallel Computational Fluid Dynamics

Simon Cox, Stephen Turnock, Alexander Phillips (Investigators), James Hawkes

Computational Fluid Dynamics (CFD) is a numerical method for modelling fluid flows and heat transfer - and is used in many industries. It can be used to model dynamics around aircraft, ships and land vehicles; and also has uses in engine design, architecture, weather forecasting, medicine, computer-generated imagery (CGI) and much more. To harness the full power of CFD, it is necessary to utilise the full power of modern supercomputers. This project aims to improve the scalabilty of existing CFD codes so that more complex problems can be tackled efficiently.

Pushing the Envelope of Planetary Formation and Evolution Simulations

Peter Bartram

A full understanding of the formation and the early evolution of the Solar System and extrasolar planetary systems ranks among natural science's grand challenges, and at present, even the dominant processes responsible for generating the observed planetary architecture remain elusive.