Bristol-based Graphcore ranked number one on Fast Company’s top 10 most innovative AI companies of 2020 list. Nvidia, for comparison, ranked fifth.

Fast Company’s confidence in Graphcore clearly isn’t misplaced. Announcing its GC200 processor, Graphcore says its new chip is the world’s most complex.

The GC200 processor boasts 59.4 billion transistors and takes the crown from Nvidia’s A100 as the world’s largest. The A100 was announced by Nvidia earlier this year and features 54 billion transistors.

Each GC200 chip has 1,472 independent processor cores and 8,832 separate parallel threads, all supported by 900MB of in-processor RAM.

Graphcore says that up to 64,000 of the 7nm GC200 chips can be linked to create a massive parallel processor with around 16 exaflops of computational power and petabytes of power. Such a system would be able to support AI models with trillions of parameters.

“We are impressed with Graphcore’s technology for energy-efficient construction and execution of large, next-generation ML models, and we expect significant performance gains for several of our AI-oriented research projects in medical imaging and cardiac simulations,” comments Are Magnus Bruaset, Research Director at Simula Research Laboratory.

“We are also pursuing other avenues of research that can push the envelope for Graphcore’s multi-IPU systems, such as how to efficiently conduct large-scale, sparse linear algebra operations commonly found in physics-based HPC workloads.”

The GC200 is just the second chip to be launched by Graphcore. Compared to the first generation, the GC200 delivers an up to 9.3x performance increase.

Graphcore’s founders believe the IPU approach that the company is taking is more efficient than Nvidia’s GPU route. The ability to scale up to thousands of IPU processors in existing compute infrastructures could mean that the cost could be 10-20x lower than using GPUs.

Back in February, Graphcore announced that it had raised $150 million in funding for its R&D. The company’s total valuation is $1.95 billion.

Graphcore was fortunate to have secured its cash before the COVID-19 pandemic really hit – with many startups reporting difficulties obtaining vital funding where there was previous interest. Undoubtedly, the GC200 will help to power research to get us through this pandemic and all the other challenges the world faces now and in the future.

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Sequoia Capital has previously invested in companies such as Apple, Google, and WhatsApp. The investor has now led a $50m (£38.2m) funding round in Graphcore — which has its headquarters in Bristol, UK.

Dedicated AI chips are set to boom in the coming years with implementation in smartphones, connected vehicles, IoT devices, and more. Back in September, we posted an editorial analysing the extent of which they’re about to take off.

In the piece, we highlighted the excitement from investors. Chip giant Nvidia has been moving into AI and the revenue from this side of the business has more than made up for its shortfall in gaming — which is often cyclical in nature.

“AI is the most important technology development of our time, with the greatest potential to help society,” says Nvidia Corp. Chief Executive Jensen Huang. “As the world’s leading cloud providers deploy the world’s best AI platform, with Volta GPUs and Nvidia software, we’ll see amazing breakthroughs in medicine, autonomous transportation, precision manufacturing and much more.”

As a result, of any business in S&P 500 Index, Nvidia had the largest stock increase in 2016. The company’s shares increased 227 percent over the previous year.

“Machine intelligence will cause an explosion of new applications and services that will transform every industry,” comments Matt Miller, partner at Sequoia, who will join the Graphcore board of directors. “The unique nature of this workload and scale of this opportunity creates an opening where a valuable new chip company can be created.”

Graphcore is reaping the benefits of the appetite for dedicated AI chips. This latest round of funding is in addition to a previous in July from some of the world’s leading AI experts — including the founder of Cambridge-based DeepMind, and Uber’s chief scientist.

“Efficient AI processing power is rapidly becoming the most sought after resource in the technological world,” says Nigel Toon, CEO at Graphcore. “The performance of Graphcore’s processor, compared to other accelerators, is going to be transformative whether you are a medical researcher, roboticist, online marketplace, social network, or building autonomous vehicles.”

We’re already seeing adoption of dedicated AI chips in smartphones. Huawei is making a promising start with the Mate 10 Pro and Google is releasing a dedicated Android Neural Network API early next year as part of its vision to build an open AI ecosystem.

The next year is going to be exciting as the adoption of AI chips accelerates. We’ll keep you updated with all developments.

What are your thoughts on dedicated AI chips?

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