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Mythic Multiplies in a Flash

August 28, 2018

Author: Mike Demler

Mythic is an AI-processor startup that uses embedded flash memory to store neural-network weights as analog parameters. The technique can store a complete neural-network on-chip, eliminating cost and power associated with DRAM. The company’s initial target is neural-network inference in low-power clients, beginning with smart cameras. We estimate the company has about 50 employees, divided between Texas and Silicon Valley.

By performing multiplication operations directly in flash memory, thus eliminating DRAM read/write cycles, Mythic estimates it can match the accuracy of inference engines running on GPUs but at a fraction of the power. Many neural networks store 10 million to 100 million weights or more in DRAM, since there are far too many to store in an inexpensive client processor. For example, the popular ResNet-50 uses more than 25 million weights. But Mythic’s prototype runs that network using just 5MB of on-chip SRAM, consuming less than 5W.

The company traces its origin to 2012 at the University of Michigan, where CTO Dave Fick completed his doctoral degree and CEO Mike Henry spent two and a half years as a visiting scholar. Over the past two years, it has attracted more than $55 million from a group that includes Lockheed Martin and SoftBank along with venture-capital (VC) firms and individual investors. Mythic plans by the end of this year to tape out its first product, which can store up to 50 million weights. At that time, it also aims to release the alpha version of its software tools and a performance profiler. The company expects to begin volume shipments in 4Q19.

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