The EIDF is the set of high-powered computational and data services that underpins the Data-Driven Innovation Programme (DDI) of the Edinburgh & South-East Scotland City Region Deal.
The EIDF GPU service is available as part of EIDF’s catalogue of resources. This containerised platform enables users to access the power of NVIDIA A100 GPUs to drive their own bespoke software environments, accelerating and deepening research insights. By using containers, researchers can develop and define their application runtime environment in a lightweight, portable, and distributable form to run on scalable platforms.
The EIDF GPU Service is now available for University of Edinburgh researchers and DDI Programme partners.
About the service
The Edinburgh International Data Facility GPU Service comprises 20 Apollo 6500 GPU servers containing 160 NVIDIA A100 GPUs, with up to 12 GPUs available for individual projects. The service is accessed through a Virtual Machine (VM) that is set up for each project within the EIDF Data Science Cloud and is operated via Kubernetes, an open-source system for automating the management of containerised applications.
The GPU Service in action
The University of Edinburgh’s School of Informatics was an early adopter of the EIDF GPU Service and helped to shape and validate it. Here users describe how it has benefited their research projects:
“The EIDF GPU Service offers a large number of computing resources, enabling me to execute computationally demanding experiments in parallel. This resource is particularly advantageous when undertaking extensive hyperparameter searches, which are crucial for obtaining conclusive answers to our research questions.” Aryo Gema, Centre for Doctoral Training in Biomedical Artificial Intelligence.
“The EIDF GPU Service has been indispensable to our research. It has equipped us with the power needed to train computationally demanding models and evaluate different efficiency strategies. Compared to earlier or alternative services, the EIDF GPU Service provides superior hardware in the form of A100 NVIDIA GPUs, which significantly expedite the research process.” Piotr Nawrot, Centre for Doctoral Training in Natural Language Processing, Institute for Language, Cognition and Computation.
“The EIDF GPU Service is enabling us to explore new methods for training more explainable, robust, and trustworthy AI systems; to design and experiment with models that can learn to search for the information they need for solving arbitrary knowledge-intensive tasks; and to design statistical models for solving challenging biomedical and clinical problems.” Pasquale Minervini, Lecturer in Natural Language Processing at the School of Informatics, supervised both projects.