Machine-learning accelerator chip to speed image recognition

SAN JOSE, Calif. — A startup will sample before June a 13-W machine-learning accelerator for cars, robots, and drones said to handily beat Nvidia GPUs in recognizing images. Visteon is considering using the chip in future automotive systems based on test results on an FPGA version of the device.

AlphaICs designed an instruction set architecture (ISA) optimized for deep-learning, reinforcement-learning, and other machine-learning tasks. The startup aims to produce a family of chips with 16 to 256 cores, roughly spanning 2 W to 200 W.

The market is already getting crowded with AI accelerators from startups and established companies, but money is still flowing into the space because AI represents a historic shift in computing. Rather than try to build large arrays of multiple-accumulate units as many early AI startups did, AlphaICs is part of an emerging group of startups that aims to take a broader look at a wider class of machine-learning algorithms and ways to speed them up.

The startup was formed by Vinod Dham, a veteran of several x86 designs, along with technical and business co-founders based in India.

“We are on a quest to build a new type of compute engine … there has to be a better architecture for deep learning, reinforcement learning, and new types of machine learning,” said Dham, who designed Pentium processors at Intel and then formed processor startups NexGen and Silicon Spice, sold to AMD and Broadcom, respectively.

AlphaICs’ first product, the 13-W RAP-E, does inference and some learning on devices at the network’s edge and should be in production late next year. A higher end RAP-C will be a 100-W chip using high-bandwidth memory for building large neural-networking models in data centers and will be in an FPGA version by June.

So far, the 25-person startup based in Bangalore raised about $15 million, enough to tape out its RAP-E in a TSMC 16FF process. It aims to raise a Series B over the next nine months to fund work on a 7-nm version of RAP-C. 

The RAP chips include both a pool of homegrown processors and multiply-accumulate arrays on a crossbar switch. (Image: AlphaICs)

The RAP chips include both a pool of homegrown processors and multiply-accumulate arrays on a crossbar switch. (Image: AlphaICs)

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