The Benefits of using Bede for N8 Researchers
"I currently run a £4M EPSRC prosperity partnership, and further EPSRC grants are being written based on the work we have been able to do with Bede." Mark Wilson, Durham University
" In using Bede, we have been able to generate results that we would not be able to obtain elsewhere. Bede allows us to run larger simulations and better explore the parameter space of interest. These undoubtedly lead to better science. Moreover, access to Bede provides opportunities for my group members to develop stronger GPU computing skills." Halim Kusumaatmaja, Durham University
"Bede is essential for producing the main data for our lab, it has meant we have been able to produce high-quality publications that have supported several grant applications." Agnes Noy, University of York
"Using Bede led to successful follow-on funding and enabled us to establish Newcastle University's expertise in the areas of force field development and computer-aided drug design. The projects below build on these research areas by taking new directions in force field research and/or supporting the UK biomolecular research community's hardware/software needs." Daniel Cole, Newcastle University
"Bede has definitely been useful in our research. Based on the outcomes of the work on Bede, we were able to secure further computing allocations on Archer2, which led to PhD studentships." Ajay B Harish, University of Manchester
"Bede allowed access to large computational power and GPU acceleration of our calculations, which were very beneficial for our project. We are using the outcomes of this research to apply for further funding." Antreas Kalli, University of Leeds
"Using Bede has allowed me to apply for further research funding. Access to GPU resources has enabled rapid prototyping and pilot studies, which are essential for developing competitive proposals. In particular, it has helped me advance new ideas in MLIP for modeling ion transport and excited-state chemistry, laying the groundwork for future grant applications." Ioan-Bogdan Magdau, Newcastle University
"We would not have been able to undertake the range and complexity of computational studies required for this work without access to Bede." Peter Jimack, University of Leeds
"We have chained several projects in part thanks to the research we performed on BEDE, for instance, our Glaucoma care project, funded by the Dunhill Medical Trust, came after our MRC-funded OCTage project." Jaume Bacardit, Newcastle University
"Bede was the main computer used for testing the performance of CASINO with and without offloading to a GPU. The project could not have been carried out with access to such a facility." Neil Drummond, Lancaster University
New projects in 2026
These projects have registered to use Bede in 2026. Find out about them by following the university links above.
| Project Title | Principal Investigator |
|---|---|
| Sustainable AI Data Compression Study: Profiling BOA on BEDE |
Caterina Doglioni Manchester |
| Solve Wind Dispersion at Street-Canyon Resolution |
Alessandro De Rosis Manchester |
| Safety-Aligned Agentic AI for Clinical Decision Support |
Mobarak Hoque Manchester |
| Correlated Motion in Solid Electrolytes |
Vanessa Ward Durham |
| Accurate machine learning potentials with autoencoders |
Richard Bryce Manchester |
| Enhancing Performance and Energy Efficiency of Tsetlin Machines |
Shounak Chakraborty Durham |
| Advanced modelling of wind farm flows |
Majid Bastankhah Durham |
| AI-ExWave: Machine learning for extreme ocean waves |
TimTang Manchester |
| Manifold Galerkin Learning for Turbulent Flows |
Miguel Beneitez Manchester |
| GPU-Accelerated Surrogate Modelling for Complex Simulations |
Congye Wang Lancaster |
| Mapping Linguistic Diversity Across NLP Research Areas |
Tharindu Ranasinghe Lancaster |
| Scalable Curvature Methods for RL Policy Optimization |
Yihe Zhou Manchester |
| Expectation-Maximization Methods for Policy Optimization |
Adrian Mircea Nenu Manchester |
| Simulating Superconductors for Fusion Power using TDGL |
Damian Hampshire Durham |
| Automated Biomechanical Pipelines for Personalized Diaphragm |
Manish Chauhan York |
| Agent World Model |
Alexandra Cristea Durham |
| Deep Learning-Accelerated Crystallography Pipeline |
Paul Niklas Ruth Durham |
| Virtual Population Simulation for Glucose-Insulin Dynamics |
Steven Johnson York |
| Generative Diffusion Model for Air Quality Forecasting |
Congbo Song Manchester |
| Conformer-Based Long-Tail Automatic Chord Recognition |
Facundo Franchino York |
|
Machine Learning to Improve the Performance of Hearing Aids |
Robert Sutherland Sheffield |