Startup Mythic (Austin, Texas) aims to compute neural-network jobs inside a flash memory array, working in the analog domain to slash power consumption. It aims to have production silicon in late 2019, making it potentially one of the first to market of the new class of chips.
“Most of us in the academic community believe that emerging memories will become an enabling technology for processor-in-memory,” said Suman Datta, who chairs the department of electrical engineering at Notre Dame. “Adoption of the new non-volatile memories will mean creating new usage models, and in-memory processing is a key one.”
In-memory computing could dramatically speed up AI
Posted on Tuesday, May 01 2018 @ 10:13 CEST by Thomas De Maesschalck
Austin, Texas based startup Mythic is working on delivering huge performance boosts for machine learning by taking a new look at a decade-old processor architecture. EE Times writes the firm believes in-memory computing could speed up artificial intelligence workloads by up to 10,000x versus what's possible with today's GPUs. Mythic isn't the only one working on this, but could be the first to make it to market. The company's first production silicon is anticipated in late 2019: