High Performance Computing

High Performance Computing​ and Scientific Computing @ Durham's Computer Science

We study the Science of Computing behind Computational Sciences.

Scientific computing has become the foundation of many areas of science. It is computer simulations that allow various application areas to progress. In this context, high performance computing is a catalysator for insights-through-computing. With new hardware generations arriving, it emancipates from a nice-to-have feature into a mandatory craft in many disciplines.

Our research goes beyond application-specific number crunching, code analysis and tuning, i.e. it goes beyond the scientific computing and HPC research found in many application areas. Instead, it searches for innovative algorithms, algorithmic paradigms, patterns, and methodolgies to meet next generation’s supercomputing challenges, and it investigates into the foundations of scientific computing as a whole.

At the moment, our major contributions are made in the area of

  • domain-specific languages for numerical simulations,
  • algorithms behind efficient multiscale methods, and
  • adaptive mesh refinement.

Research highlights

  • Researchers from Durham’s CS HPC team are a driving force behind the development of Firedrake.
  • Durham’s HPC team is the virtual home of the Peano framework.
  • The European Union’s H2020 project ExaHyPE is actively driven by our HPC researchers.

The group actively collaborates with various compute-heavy departments in Durham. Highlights are joint projects, activities and research with the Department of Mathematics, the Physics department with its Institute for Particle Physics Phenomenology and  its Institute for Computational Cosmology. Further links with Earth Sciences and the Department of Engineering yield interesting research. HPC’s most active interdisciplinary activities are typically organised under the umbrella of the Institute for Data Science.

Our researchers rely on Durham’s own supercomputer Hamilton, they have access to a 3x15m 3d visualisation wall, and we host several experimental workstations. By the end of 2019, we plan to purchase our own Mellanox BlueField cluster in collaboration with the DiRAC consortium.



Dr Tobias Weinzierl

Associate Professor

Associate Professor in the Department of Computer Science

Telephone: +44 (0) 191 33 42519

Contact Dr Tobias Weinzierl (email at tobias.weinzierl@durham.ac.uk)


T. Weinzierl: A Framework for Parallel PDE Solvers on Multiscale Adaptive Cartesian Grids. Verlag Dr. Hut, München, 2009.

This book is available online though I very much appreciate if you buy it from the publisher.


M. Bader, H.-J. Bungartz and T. Weinzierl (ed.): Advanced Computing, Volume 93 of Lecture Notes in Computational Science and Engineering. Springer-Verlag, Heidelberg, Berlin, 2013.

Indicators of Esteem

Research Groups

  • Innovative Computing

Research Interests

  • High-performance Computing
  • Parallel Algorithms
  • Scientific Computing

Selected Publications

Journal Article

Authored book

Chapter in book

Conference Paper

  • Atanasov, Atanas, Srinivasan, Madhusudhanan & Weinzierl, Tobias (2012), Query-driven Parallel Exploration of Large Datasets, Large Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on. 23 -30.

Newspaper/Magazine Article

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Related Links


Mr Charles Murray

PhD student
Postgraduate Student in the Department of Computer Science

(email at c.d.murray@durham.ac.uk)

Is supervised by

Mr Meshal Alharbi

PhD student
PhD Student in the Department of Computer Science

(email at meshal.g.alharbi@durham.ac.uk)

Selected Publications

Journal Article

Show all publications

Is supervised by

Mr Henry Westmacott

PhD student

I am a 1st year PhD student in computer science at Durham University. Currently researching methods for enhanced diagnostic output and performance from the gridless scatter correction system in development by IBEX Innovations Ltd.

Is supervised by

Dr Lawrence Mitchell

Assistant Professor
Assistant Professor in the Department of Computer Science

(email at lawrence.mitchell@durham.ac.uk)


I am an Assistant Professor in the Department of Computer Science at Durham University. My research is in high performance computing and computational mathematics. Much of my recent focus has been in the development of compilers and software abstractions for the development of numerical models implemented using the finite element method. This research is concretely realised in the open source Firedrake project. I am particularly interested in preconditioning techniques for challenging problems in computational and atmospheric fluid dynamics.

Research interests

The focus of my work is how to address the increasingly sophisticated needs of computational science practitioners by changing the way we think about numerical models. I develop computational mathematical abstractions that enable the automation of efficient implementations of complex, multiscale, numerical methods on modern supercomputers.

Compilers for numerical software

In the Firedrake project, I work on capturing the mathematical abstractions in numerical models, blending symbolic reasoning and numerical computation. This enables an approach to numerical software development that leverages symbolic information to synthesise high performance, parallel implementations of mathematical algorithms. This is possible through careful design of software abstractions, and development of domain-specific optimising compilers.

Fast solvers for geophysical flows

A large part of sophisticated numerical model development is in the design of robust linear and nonlinear solvers for the equations of interest. I have a particular interest in fast solvers for structure-preserving discretisations in atmospheric fluid dynamics. With Eike Müller, I developed a mesh-, and parameter- independent multigrid scheme for the mixed finite element discretisation proposed for the UK “GungHo” Dynamical Core project. We are presently working on multilevel schemes for the hybridised formulation of these equations, which should permit faster solvers. This latter work is in close collaboration with Colin Cotter, and Thomas Gibson.

Research Groups

  • Innovative Computing

Selected Publications

Journal Article

Working Paper

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Peter Noble

PhD Student

(email at peter.noble@durham.ac.uk)

Is supervised by


We are hiring! The official post description can be found at the Computer Science homepage (pick the second advert in the row), but here’s the deep link (PDF).