UCL today announced that it has been named a GPU Research Centre by NVIDIA, the world leader in visual computing.
GPU Research Centres are institutions that embrace and utilise GPU technologies across multiple research fields, and are at the forefront of some of the world’s most innovative scientific research. GPU accelerated computing leverages the parallel processing capabilities of GPU accelerators and enabling software to deliver dramatic increases in performance for scientific, artificial intelligence, deep learning, graphics, engineering, and other demanding applications.
UCL was recognised for its advanced research in a wide variety of areas, including bio-molecular modeling for cancer research, vascular imaging and magnetic resonance physics, computational systems biology, tsunami modeling, image registration, finite element modeling and image guided surgery, to name a few. In addition, as a member of the SES (Science and Engineering South) consortium, a world-leading science and engineering research hub formed by 5 leading research-intensive universities, UCL researchers have access to the EMERALD GPU cluster, one of the largest in Europe (see some case studies).
Researchers across campus came together to put in a UCL-wide bid, with the application led by Dr Matt Clarkson (Translational Imaging Group, Centre for Medical Image Computing), Daghan Cam (UCL Bartlett School of Architecture), Dr James Hetherington (UCL Research Software Development Group) and Prof Sebastien Ourselin (UCL Institute of Biomedical Engineering).
Daghan Cam, Leader of GPU Computing Research at UCL’s Bartlett School of Architecture, says: “The college’s wide initiative and partnership with NVIDIA is enabling cross-disciplinary collaborations and accelerating our research in many areas like real-time simulations, computational physics and deep learning, as well as practical applications such as computer vision for robotics and 3D printing.”
James Hetherington, Head of Research Software Development at UCL, adds: “NVIDIA’s GPU accelerator technologies provide an opportunity for researchers to realise transformative performance gains. In the Research Software Development Group we try to help researchers create code which supports scholarly communication and builds for the long term. We’re delighted that as a GPU Research Centre UCL researchers will be able to work with NVIDIA’s expert programmers to build CUDA code that is fast, readable and reliable.”
As a GPU Research Centre, UCL will have pre-release access to NVIDIA GPU hardware and software, the opportunity to attend exclusive events with key researchers and academics, a designated NVIDIA technical liaison, and access to specialised online and in-person training sessions. GPU Research Centres were formerly known as CUDA Research Centres.