JADE: Joint Academic Data science Endeavour

Lead Research Organisation: University of Oxford
Department Name: Mathematical Institute


This proposal led by the University of Oxford, with support from the Alan Turing Institute (ATI), Bristol, Edinburgh, KCL, QMUL, Sheffield, Southampton and UCL is for a national GPU system that will support multidisciplinary science with a focus on machine learning and molecular dynamics. The architecture is based on ``fat'' GPU compute nodes, with 8 of NVIDIA's new Pascal GPUs, each with
a) 16GB 720GB/s HBM2 memory,
b) an 80GB/s NVlink interconnect to other GPUs,
c) 6GB/s bandwidth to main system memory,
d) 6GB/s bandwidth to the Infiniband external network.
Each server also has two 20-core Xeons, 512 GB DDR4 memory and 8TB SSD.

The motivation for selecting this architecture is the huge growth in research in machine learning and associated areas of data science within the UK, particularly within the universities which are members of the Alan Turing Institute, or SES. The same architecture is also ideally suited for molecular dynamics, medical imaging and a number of other application areas.

The system will be run as a national facility, similar to Archer in being free to all academic users with computing time available to all through a lightweight Resource Allocation Panel, with a top-level steering committee determining the policy on resource allocation between the different application areas (Machine Learning, Molecular Dynamics, Other).

Planned Impact

One outcome from this investment in a national GPU system will be an increased number of researchers leaving universities with excellent GPU computing skills. This will have a significant impact on the UK economy in a number of key market sections:

a) Machine Learning

Many companies such as Google, Microsoft, Baidu and Facebook use GPUs extensively for machine learning applications because they are the most cost-efficient hardware platform for such applications. Within the UK, Google Deepmind, which was originally a UCL spinoff company, is the most important of these, but machine learning is also being used in a wide variety of startups.

b) Computer Vision and Self-Driving Cars

This is a research area which is growing very rapidly and will have a huge impact in the near future. Again there is a mix of companies working the area, ranging from multi-nationals such as Audi to UK startups such as Oxbotica, an Oxford spinoff company.

c) Oil and gas sector

GPUs are used extensively for both seismic inversion (in the exploration phase) and oil reservoir simulation (to maximise the production yield), with over 500 GPUs being used for this purpose within the UK.

d) Pharmaceuticals

There has been some noteworthy use of GPUs in drug discovery, checking the potential of new drugs by comparing their characteristics to other similar chemical compounds.

e) Finance sector

GPUs are used heavily by the big investment banks, with over 2500 in use at various big banks in London.

f) Creative / media companies

These companies, which include film and computer games companies, contribute £2.5bn to the UK economy, and parts of the sector use GPUs extensively for games, and special effects in films and commercials.


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