PALO ALTO, Calif.--A handful of semiconductor-industry refugees on
Monday (Oct. 29) unveiled their grid-optimization startup with fresh
venture capital funding and the launch of a software product that
uses big data to improve power power use and cut costs for utilities
Auto Grid, a year-old, 15-person company located a block from the
historic former Fairchild Semiconductor building, nabbed $9 million
venture funding from Foundation Capital, Voyager Capital and
Stanford University. Simultaneously it launched its
Energy Data Platform (EDP) software platform for mining smart
meter and other utility data and its
Its Demand Response Optimization and Management Systems
(DROMS), a software-as-a-service platform aimed at easing the
costs to utilities of implementing demand response programs
while increasing the “yield” of these programs.
The company was founded by Amit Narayan, former R&D chief at
Magma Design Automation and founder of Berkeley Design Automation.
He's joined on his management team by Chris Knudsen, CTO, and Andy
Tang, vice president of business development, both formerly with
Intel's WiMax divisiion and Pacific Gas & Electric (PGE). Former
engineers in EDA and at National Semiconductor also work on the
"Now that we have all these devices...and they're all connected and
bringing data to the utilities and service providers, there are very
few applications that are able to take advantage of this data,"
Narayan said in a press conference. "In fact most utilities and
service providers are not even equipped to deal with this tsunami of
That data, on a 10,000-meter network can range from 32 Gbytes per
years to 114.6 terabytes, depending on the how frequently the data
is captured. In a network of 100,000 smart meters, it can be as much
as 1.1 petabytes.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.