Cerebras Expands AI Training & Inference Cluster in Europe at the University of Edinburgh to Accelerate AI Research and UK’s AI Capabilities
EDINBURGH, Scotland & SUNNYVALE, Calif.–(BUSINESS WIRE)–Today the University of Edinburgh and Cerebras Systems announced the successful installation and service start of a groundbreaking Cerebras CS-3 system cluster at the University. Operated by EPCC, the supercomputing centre at the University, and part of the Edinburgh International Data Facility, the cluster consists of four CS-3s using Cerebras’s latest 3rd generation of Wafer Scale Engine processors – the world’s largest commercially available AI chip ever built.
The new service, which builds on experience EPCC gained with the Cerebras CS-1 and CS-2 systems, is a key part of the AI service provided to the Edinburgh and SE Scotland City Region as part of the Data Driven Innovation programme, which has been led by the University since 2018.
Professor Mark Parsons, EPCC Director, said:
AI is transforming all of our lives, and this investment will help universities, public sector organisations, and companies – large and small – to train and use AI models at speeds and with ease no other AI technologies can match,
“When we started our collaboration with Cerebras in 2020, the company’s technology focused on training AI models at scale. With the Cerebras CS-3 systems, we can now take advantage of Cerebras AI Inference – the company’s record-breaking inference technology. EPCC has always worked at the leading edge of supercomputing and our investment in this system brings a uniquely powerful AI resource to our region.”
With the new Cerebras CS-3 cluster, EPCC is now able to train models ranging from 240 billion to 1 trillion parameters. It can fine-tune 70 billion parameter model in a day. The ease of use of Cerebras’s technology allows for a more democratic approach to AI models – scientists and ML practitioners from other disciplines, not only computer science, can start training and using models with no need for complex parallel programming. The ability of Cerebras’s technology to scale linearly allows for unmatched innovation, iteration, and productivity for the EPCC team.
Additionally, Cerebras CS-3s deliver industry-leading AI inference, enabling EPCC to run state-of-the-art models at speeds unachievable with GPUs. Cerebras Inference runs the industry’s most popular models at more than 2,000 tokens/s – up to 70x faster than leading GPU solutions.
Andrew Feldman, CEO and co-founder, Cerebras, said:
We are honored to expand our multi-year partnership with EPCC with this new CS-3 cluster, which will be a major leap forward in advancing AI research and capabilities in the UK,
“EPCC has done pioneering work in enabling the next generation of AI breakthroughs. With this latest installation in the European continent, we’re excited to be part of such an important initiative that will enable researchers and institutions to drive innovation and shape the future of AI and HPC at a scale previously thought impossible.”
The University of Edinburgh has been a world-leader in AI for the past 60 years. The CS-2 systems at EPCC have already enabled researchers at the University to develop highly optimised wafer-scale inference software for Large Language Models (LLMs), to explore their use for biomedical AI, and for local company, smartR AI™ to explore fine-tuning of LLMs on the system. The EPCC systems have also helped researchers in India to develop an LLM for materials science and, in Switzerland, to adapt LLMs to better support Swiss German dialects. With 3.6 million AI compute cores, the CS-3s will also enable EPCC to continue its AI research into parallelism and energy efficiency.
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Cerebras Expands AI Training & Inference Cluster in Europe at the University of Edinburgh to Accelerate AI Research and UK’s AI Capabilities, source
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