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Intel Scales Neuromorphic Research System to 100 Million Neurons

SANTA CLARA, Calif.--(BUSINESS WIRE), Mar. 18, 2020 – 

What's New: Today, Intel announced the readiness of Pohoiki Springs, its latest and most powerful neuromorphic research system providing the computational capacity of 100 million neurons. The cloud-based system will be made available to members of the Intel Neuromorphic Research Community (INRC), extending their neuromorphic work to solve larger, more complex problems.

"Pohoiki Springs scales up our Loihi neuromorphic research chip by more than 750 times, while operating at a power level of under 500 watts. The system enables our research partners to explore ways to accelerate workloads that run slowly today on conventional architectures, including high-performance computing (HPC) systems."

–Mike Davies, director of Intel's Neuromorphic Computing Lab

What It is: Pohoiki Springs is a data center rack-mounted system and is Intel's largest neuromorphic computing system developed to date. It integrates 768 Loihi neuromorphic research chips inside a chassis the size of five standard servers.

Loihi processors take inspiration from the human brain. Like the brain, Loihi can process certain demanding workloads up to 1,000 times faster and 10,000 times more efficiently than conventional processors. Pohoiki Springs is the next step in scaling this architecture to assess its potential to solve not just artificial intelligence (AI) problems, but a wide range of computationally difficult problems. Intel researchers believe the extreme parallelism and asynchronous signaling of neuromorphic systems may provide significant performance gains at dramatically reduced power levels compared with the most advanced conventional computers available today.

What the Opportunity for Scale is: In the natural world even some of the smallest living organisms can solve remarkably hard computational problems. Many insects, for example, can visually track objects and navigate and avoid obstacles in real time, despite having brains with well under 1 million neurons.

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