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Graphcore unveils new GC200 chip and the expandable M2000 IPU Machine that runs on them

There is a lot riding on the use of artificial intelligence technology to help us take giant leaps onward in resolving complex challenges — whether it’s medical breakthroughs, constructing better cybersecurity, or better sailing structures for automobiles and other moving objectives. But the well advanced the employment, “the worlds biggest” the need for hardware that can handle the calculations and treating; and that intends the race is on for ever-more powerful processing. Now, the UK startup Graphcore is announcing its latest contribution to that effort.

Today, it is announcing a brand-new chip, the GC200, and a new IPU Machine that runs on it, the M2000, which Graphcore says is the firstly AI computer to achieve a petaflop of processing dominance” in the size of a pizza casket .”

Graphcore says that there are no plans for the GC200 to be sold separately, and it will come only in the M2000. Nigel Toon, the CEO and co-founder, said the M2 000 is now shipping to early access customers and will be more widely by the end of this year to clients in works in areas like financial services, healthcare, technology and more,” wherever AI is used .”

This is the second generation of Graphcore’s hardware to be exhausted, and its first in exactly under two years, Toon notes.

The IPU Machine uses four members of the 7nm GC200 IPU microchips, with the GC200 featuring 59.4 billion transistors on each microchip. Potentially, Graphcore says that up to 64,000 IPUs can be connected together to create a vast parallel processor of up to 16 exaflops of estimating influence and petabytes of memory to patronize simulations with trillions of constants. The notion is that these can be scaled up as necessary.

The moves come at a key time both for Graphcore and the AI hardware industry. The UK upstart participates against leviathans in the world of processors like Nvidia and Intel — Graphcore conjured a further $ 150 million in May at a nearly$ 2 billion valuation to compete against them, and Toon says the $450 million it’s developed so far is enough for now, with customers like Microsoft and others already on its books — but also a plethora of other business constructing AI chips. And it was only in May that Nvidia unveiled its own latest chip, the A100, its first Ampere-based GPU that hopes 5 petaflops of performance.

Graphcore and its manager Toon — who, with his co-founder Simon Knowles, had sold a previous startup announced Icera to Nvidia — argue that its IPU approach is more efficient and boosted than the GPU route that Nvidia is taking.

” We are trying to build products that are easy to put into your existing compute infrastructure ,” he said.” It means you can scale up to thousands of IPU processors .” And, he computed, that means that the cost of ownership can be 10 -2 0 times less for the IPU approach, which in turn translates to faster take-up of the hardware.

Toon says that while other chipmakers continue to work on a number of other processing applications in latitude with AI — for example for portable inventions, or quantum chippings — Graphcore is remaining securely focused on AI employments, which he says is still in” massive the possibilities for us to grow our business and add more clients .”

” We’re 100% focused on silicon processors for AI, and on house systems that can plug into existing cores. Why would we want to build CPUs or GPUs if those previously progressing well? This is just a different toolbox .” He said he believes it will be a 10 -1 5 year opening before quantum or molecular computing to come along, a trajectory that might constitute a great deal of challenges for smaller startups trying to build in that area against biggies like IBM.

Toon noted that AI stands among the trends that the COVID-1 9 pandemic has accelerated — not only around the many applications being pursued around the health crisis and fighting the virus itself, but likewise around cultivating and improvement of processes for other services resulting from that.

” We’ll probably burn $100 million more investing in technology and parties” — the company now has 450 hires, Toon memorandum,” but our revenues are also ramping, and the $300 million in cash we have today should be sufficient to get us to a a fast and profitable business .”

Read more: feedproxy.google.com

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