Efficiency – Flex Logix’s Update on InferX™ X1 Edge Inference Co-Processor

Efficiency – Flex Logix’s Update on InferX™ X1 Edge Inference Co-Processor
by Randy Smith on 10-30-2019 at 10:00 am

Last week I attended the Linley Fall Processor Conference held in Santa Clara, CA. This blog is the first of three blogs I will be writing based on things I saw and heard at the event.

In April, Flex Logix announced its InferX X1 edge inference co-processor. At that time, Flex Logix announced that the IP would be available and that a chip,… Read More


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

AI Hardware Summit, Report #2: Lowering Power at the Edge with HLS
by Randy Smith on 09-30-2019 at 10:00 am

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 Mentor, a Siemens Business.… Read More


Semicon West 2019 – Day 2

Semicon West 2019 – Day 2
by Scotten Jones on 07-18-2019 at 10:00 am

Tuesday July 9th was the first day the show floor was open at Semicon. The following is a summary of some announcements I attended and general observations.

AMAT Announcement

My day started with an Applied Materials (AMAT) briefing for press and analysts where they announced “the most sophisticated system they have ever released… Read More


DSP-Based Neural Nets

DSP-Based Neural Nets
by Bernard Murphy on 10-24-2017 at 7:00 am

You may be under the impression that anything to do with neural nets necessarily runs on a GPU. After all, NVIDIA dominates a lot of what we hear in this area, and rightly so. In neural net training, their solutions are well established. However, GPUs tend to consume a lot of power and are not necessarily optimal in inference performance… Read More