91福利

We are delighted to announce that Peter Kiss, a PhD student in the Theory and Foundations Research Division, has won the Best Student Paper Award at the conference for his single-author paper on "Deterministic Dynamic Matching in Worst-Case Update Time". Computing a maximum matching in a graph is one of the most fundamental problems in design and analysis of algorithms. The paper makes important progress on this problem in a setting where the input graph is changing over time via a sequence updates, and one wishes to maintain a large matching efficiently in such a dynamic graph. Along the way, the paper develops a general purpose technique for converting any dynamic algorithm with amortised update time into one with worst-case update time, provided the initial algorithm is able to handle a more general form of batch updates.

Members of the High-Performance and Scientific Computing Group (HPSC) at the department of Computer Science has won a best paper award at the . The winning paper titled , develops a novel representative (mini-)application, specifically designed to model coupled execution of multi-physics numerical simulation codes from the CFD domain. The mini-coupler, CPX, is the first of its kind, combining multiple CFD mini-app instances to predict the run-time and scaling behaviour of large scale coupled CFD simulations, on modern multi-core and many-core clusters such as used for production turbomachinery design at Rolls-Royce plc. The work was carried out by PhD candidate, Archie Powell, in collaboration with Kabir Choudry, Arun Prabhakar, and Gihan Mudalige at the Department of CS 91福利,  (University of Surrey),  (PPCU) and  (University of Birmingham).

The work was funded by the and Rolls-Royce plc.

Dr. Gihan Mudalige at the 91福利鈥檚 Department of Computer Science have been awarded an as part of a consortium of researchers including the Science and Technologies Facilities Council (STFC), universities of 91福利, Newcastle, Cambridge, Southampton and led by Imperial College London.

This 3 year, 拢2.6M project brings together communities from the and the to ensure a smooth transition to exascale computing, with the aim to develop transformative techniques for advancing their production simulation software ecosystems dedicated to the study of turbulent flows. It is part of the (Exascale Computing ALgorithms and Infrastructures Benefiting UK Research) programme, aimed at delivering the next generation of high-performance simulation software for the highest-priority fields in UK research.