In April, I covered a new AI inference chip from Flex Logix. Called InferX X1, this part had some very promising performance metrics. Rather than the data center, the chip focused on accelerating AI inference at the edge, where power and form factor are key metrics for success. The initial information on the chip was presented at … Read More
For a long time, memories were the primary technology driver for process development. If you built memories, you got access to cutting-edge process information. If you built other products, this could give you a competitive edge. In many cases, FPGAs are replacing memories as the driver for advanced processes. The technology… Read More
Word on the virtual street is that Wave Computing is closing down. The company has reportedly let all employees go and will file for Chapter 11. As one of the many promising new companies in the field of AI, Wave Computing was founded in 2008 with the mission “to revolutionize deep learning with real-time AI solutions that scale from… Read More
TinyML is kind of a whimsical term. It turns out to be a label for a very serious and large segment of AI and machine learning – the deployment of machine learning on actual end user devices (the extreme edge) at very low power. There’s even an industry group focused on the topic. I had the opportunity to preview a compelling webinar about… Read More
The popular Linley Processor Conference kicked off its spring event at 9AM Pacific on Monday, April 6, 2020. The event began with a keynote from Linley Gwennap, principal analyst and president at The Linley Group. Linley’s presentation provided a great overview of the application of AI across several markets. Almost all of the… Read More
Ron Lowman, product marketing manager at Synopsys, recently posted an interesting technical bulletin on the Synopsys website entitled How AI in Edge Computing Drives 5G and the IoT. There’s been a lot of discussion recently about the emerging processing hierarchy of edge devices (think cell phone or self-driving car), cloud… Read More
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
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
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
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
