The UK’s most powerful supercomputers are running software that cannot keep up with the hardware they sit on. As computing platforms evolve into complex multiprocessor systems, the numerical algorithms that drive simulations in engineering, physics, and data science are often written in ways that fail to exploit the new machines. This project brings together mathematicians, computer scientists, and parallel-computing specialists from Edinburgh, Heriot-Watt, and Strathclyde to fix that mismatch. The team will develop advanced numerical algorithms—for tasks such as high-order finite-element modelling in solid and fluid mechanics, numerical optimisation, and molecular simulation—and then encode them using smarter markup and annotation systems. New compilation techniques will shift the burden of adapting code to specific hardware from the programmer to the compiler, but with the compiler guided by annotations from the algorithm developers. If successful, this approach could make high-performance computing far more efficient across energy research, health sciences, nanoscience, and the digital economy. The project includes knowledge-exchange partnerships with HP, IBM, SGI, and industrial users such as Schlumberger and SAS, ensuring the new methods reach real-world applications.
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Advances in computing power have broadened the spectrum of applications amenable to computational treatment, but software improvements must keep pace with advances in computing technology if new hardware investment is to be fully exploited for the benefit of society. Numerical analysis is a traditional strength of UK mathematics, but it must establish new means of collaboration with computer scientists to be relevant for the fast changing platforms of high performance computing. In this well-supported and timely initiative, numerical analysts at Edinburgh, Heriot-Watt and Strathclyde Universities will work together with compiler experts from Edinburgh Informatics and specialists in parallel computing from the Edinburgh Parallel Computing Centre (EPCC) to improve the software development paradigm for implementation of numerical algorithms on diverse and evolving multiprocessor systems. By bringing mathematicians and computer scientists into close collaboration with HPC specialists, this initiative will address key issues raised in the international reviews of UK mathematics and high performance computing. Additional strategic appointments will be made by the universities, providing a sustainable, long-term commitment. Advanced numerical algorithms will be developed for state-of-the-art applications, such as high order adaptive finite elements for solid and fluid mechanics, numerical optimization, multi-scale methods, and new parallel methods for molecular simulation and data analysis. Algorithms will be coded using better systems of markup and annotation, and new compilation techniques will be introduced by the computer scientists and implemented in collaboration with researchers at EPCC. This paradigm shifts the details of implementation to compilers, but compilers informed by algorithm developers via annotation. The methods developed will have clear potential to impact the key themes of the EPSRC delivery plan, including energy, health sciences, nanoscience, and the digital economy. To strengthen the uptake of new methodology among the research base, algorithms will be tested and their performance evaluated in collaboration with applications scientists and engineers. This proposal includes knowledge exchange partnerships with major computing companies (HP, IBM, SGI) as well as industrial users of HPC algorithms (Schlumberger, Orange/France Telecom, SAS), opening new pathways for effective utilisation of new software techniques. Connections to national laboratories such as Daresbury and Rutherford Appleton are also planned. The project is further enhanced through funded connections with Cambridge University, the University of Warwick, and the Wales Institute for Mathematical and Computational Science.
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