NVIDIA Takes AI Initiative With a Supercomputer To Support UK Healthcare

Introducing Cambridge-1, a superior supercomputer in the United Kingdom to bolster UK healthcare researchers.


On Tuesday, July 6, 2021, NVIDIA announced the launch of the most powerful supercomputer in the United Kingdom of Great Britain and Northern Ireland. The healthcare research piece of technology built for the 67 million good people of the United Kingdom would inevitably be ranked one of the world's fastest AI supercomputers.

Nvidia expended 80 top drawer AI software A100 graphics card, the DGX A100 to Cambridge-1
Nvidia expended 80 top drawer AI software A100 graphics card, the DGX A100 to Cambridge-1
Key Facts
  1. 1

    The healthcare innovation's cost estimates at a whopping $100million.

  2. 2

    NVIDIA collaborated with five organizations from relevant sectors to birth this contraption

  3. 3

    Cambridge-1 has a performance rating of 8 petaflops.

  4. 4

    The supercomputer is entirely powered by renewable energy.


NVIDIA's first project with GlaxoSmithKline (GSK), a global healthcare firm headquartered in London and the sixth-largest pharmaceutical company in the world, according to Forbes in 2019, the biotechnological pharmaceutical headquartered in Cambridge, England, AstraZeneca, Guy’s and St Thomas’ NHS Foundation Trust, Oxford Nanopore Technologies, and King’s College London is centred around the fastest supercomputer ever seen in the UK since the beginning of time. This piece of AI-powered healthcare contraption cost Nvidia Corp. a breathtaking $100 million in its making.

The purpose of this supercomputer is to improve the UK's healthcare with Artificial Intelligence, empowering the digital biology revolution and bolstering the country’s life sciences industry. The world is going into a new age, or better put, this journey has been on for a while already—the journey where Artificial Intelligence has been providing answers to all questions of innovation and advancements.

About healthcare, humanity has always strived to meet up with chronic health complications, disease outbreaks, and incurable health conditions. There has been more emphasis on being steps ahead and not just meeting up, which has been demonstrated in ridding the entirety of Europe of the deadly malaria virus. However, these disease vectors have been evolving and providing more questions for healthcare researchers and scientists to answer.

An example is a COVID-19 virus, which evolved and is still evolving into various strains with deadlier symptoms than the previous. Thus seeing a $100 million healthcare investment in a country that recorded 5.06 million cases and 128,000 deaths in the most recent pandemic would not surprise many. Researchers and scientists can use Artificial Intelligence to understand brain diseases like dementia better and use AI to build novel medications and improve the accuracy of discovering disease-causing mutations in human genomes.

When consulted, Linpack measured the performance rating of Cambridge-1; the result was eight petaflops, the yardstick for measuring system speed, 1 equalling a quadrillion processing operations every second.

However, the eight petaflops result was derived from merely a series of mathematical equations. Nvidia claims that it's a whole different ballgame when running AI workloads, as its performance rating skyrockets to 400 petaflops.

Cambridge-1 draws power from renewable energy, which it taps into at a custodian facility Dan by Kao Data Ltd. Cambridge-1 is quite demanding; the water is wet. Nvidia expended 80 top drawer AI software A100 graphics card, the DGX A100 to Cambridge-1. The computing modules also gave Bluefield-2 data processing units. The SuperPOD architecture was a significant component in the design of Cambridge-1.

AstraZeneca will corporate with Nvidia to build an AI channel for breaking down chemical properties to create new medications.

GSK will make the most of Cambridge-1 to support its drug research, while St Thomas' NHS Foundation Trust and King's College London are teaching AI models to induce synthetic brain images

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