AI Hardware Summit, Report #2: Lowering Power at the Edge with HLS

Excerpt from article: “AI Hardware Summit, Report#2: Lowering Power at the Edge with HLS

I previously wrote a blog about a session from Day 1 of the AI Hardware Summit at the Computer History Museum in Mountain View, CA, held just last week. From Day 2, I want to delve into this presentation by Bryan Bowyer, Director of Engineering, Digital Design & Implementation Solutions Division at Siemens EDA. This conference brought together many companies involved in building artificial Intelligent and machine learning hardware solutions. Naturally, there were several discussions around AI software and applications as well. Day 1 of the conference was more about solutions in the data center, whereas Day 2 was primarily around solutions at the Edge.

Most solutions at the Edge have power restrictions. These often are battery-powered or energy harvesting devices such as remote cameras, robots, cell phones, and many other sensor-carrying devices. A different class of edge devices represents those devices which are always on, such as smart appliances, leading to power concerns for a different reason – because it is always on. Of course, higher power typically leads to higher heat dissipation which again will lead us to prefer lower power. At the Edge, power is critically important.

Read the entire article on SemiWiki originally published on September 30th, 2019.

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