Lattice Raises the Bar on Low Power AI

We are all focusing a lot of attention on neural network inference these days. There is lengthy debate about the relative merits of GPUs, high-end FPGAs, and other specialized solutions for generating the most and best inferencing per coloumb. Most of that centers around data center or high-end edge designs. But the real volume for inferencing chips will clearly be in cost-, power-, and space-constrained edge systems, often running on batteries, and usually far out of the realm of conventional GPUs and FPGAs. Companies like NVidia, Intel, and Xilinx are engaged in all-out war in that arena, with Xilinx announcing a new ultra-high-performance accelerator board just this week (more on that in a future article).

In this edge inferencing space, the competition is completely different, and somewhat more interesting. Lattice Semiconductor – who has carved out a solid niche in ultra-low-power programmable logic devices – has just announced a set of enhancements and upgrades to their sensAI stack offering. sensAI stack includes modular hardware platforms, neural network IP cores, software tools, reference designs, and custom design services from eco-system partners. The company says sensAI stack is aimed at “deployment of always-on, on-device AI into a range of edge applications including mobile, smart home, smart city, smart factory, and smart car products.” In particular, they are aiming at applications that can use an inferencing engine in the 1mW-1W range that costs $1-$10 USD.

We wrote about sensAI stack back when it was first announced, and this latest set of enhancements brings new capability and increased performance to the table. Specifically, Lattice is adding new IP cores, reference designs, demos, and hardware development kits. Or, in other words, exactly the kind of stuff that makes the “stack” concept interesting and useful in the first place.

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