Wave Computing CTO Chris Nichol Presents “A Novel Dataflow Processing Technology for Deep Learning” at the Linley Processor Conference 2016


CAMPBELL, Calif., Sept. 22, 2016 (GLOBE NEWSWIRE) -- Who: Wave Computing, Chris Nichol, Chief Technology Officer will present “A Novel Dataflow Processing Technology for Deep Learning”

What: The Linley Processor Conference is a two-day event focusing on system
design issues.

When: Wednesday, September 28, 2016, 9:45am – (these times are tentative)
Conference: 9:00 a.m. – 4:30 p.m., Reception: 4:30 – 6:00 p.m.

Where: Hyatt Regency Santa Clara at 5101 Great America Parkway, Santa
Clara, Calif.

Registration: www.linleygroup.com/processor-conference

“Deep learning is at a crossroads,” says Chris Nichol, Wave Computing CTO. “Existing solutions continue to push conventional Von Neumann computing architectures to meet the increasing computing demands from deep learning workloads in the data centers. Even the general purpose GPUs as compute accelerators are struggling to meet the growing demands of deep learning. Wave’s dataflow architecture, which achieves an order of magnitude increase in performance over GPU based alternatives, promises to break through this performance wall to greatly expand the headroom for deep leaning computing.”

"Processors are becoming increasingly specialized to meet the needs of their target applications, including automotive, deep learning, networking, and IoT designs,” said Linley Gwennap, principal analyst and conference chairperson. “The Linley Processor Conference gathers leading processor vendors to deliver vetted presentations about their newest solutions.  The conference also features several presentations on memory and IP cores used to develop customized processors and subsystems. These talks, plus keynote speeches and Q&A panels, give attendees the critical information they need to select the best processor technology for their designs.”

About Wave Computing, Inc.

Wave Computing was founded with the vision of delivering the world’s fastest and most energy efficient computers for the Deep Learning market. Wave is realizing this vision through the development of game-changing dataflow processing technology with unmatched compute-energy efficiency.  Backed by Tier 1 VCs, an IP portfolio including over 50 U.S. patents, and a track record of innovation, Wave is dedicated to accelerating the application of Deep Learning in the datacenter and beyond. Wave is based in Campbell, California.


            

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