Key Applications for Chip Monitoring

Key Applications for Chip Monitoring
by Daniel Nenni on 04-24-2020 at 2:00 pm

Richard McPartland

One of the side benefits of working with SemiWiki is that you get to meet a broad range of people and in the semiconductor industry that means a broad range of very smart people, absolutely. Recently I had the pleasure to meet Richard McPartland of Moortec. Richard and I started in the semiconductor industry at the same time but from… Read More


TinyML Makes Big Impact in Edge AI Applications

TinyML Makes Big Impact in Edge AI Applications
by Tom Simon on 02-12-2020 at 10:00 am

TimyML ECM3532 Architecture

Machine Learning (ML) has become extremely important for many computing applications, especially ones that involve interacting with the physical world. Along with this trend has come the development of many specialized ML processors for cloud and mobile applications. These chips work fine in the cloud or even in cars or phones,… Read More


Specialized Accelerators Needed for Cloud Based ML Training

Specialized Accelerators Needed for Cloud Based ML Training
by Tom Simon on 01-27-2020 at 10:00 am

AI Domain Specific Processor

The use of machine learning (ML) to solve complex problems that could not previously be addressed by traditional computing is expanding at an accelerating rate. Even with advances in neural network design, ML’s efficiency and accuracy are highly dependent on the training process. The methods used for training evolved from CPU… Read More


Autonomous Driving Still Terra Incognita

Autonomous Driving Still Terra Incognita
by Bernard Murphy on 12-12-2019 at 6:00 am

Whither self-driving?

I already posted on one automotive panel at this year’s Arm TechCon. A second I attended was a more open-ended discussion on where we’re really at in autonomous driving. Most of you probably agree we’ve passed the peak of the hype curve and are now into the long slog of trying to connect hope to reality. There are a lot of challenges, … Read More


Characteristics of an Efficient Inference Processor

Characteristics of an Efficient Inference Processor
by Tom Dillinger on 12-11-2019 at 10:00 am

The market opportunities for machine learning hardware are becoming more succinct, with the following (rather broad) categories emerging:

  1. Model training:  models are evaluated at the “hyperscale” data center;  utilizing either general purpose processors or specialized hardware, with typical numeric precision of 32-bit
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New Generation of FPGA Based Distributed Accelerator Cards Offer High Performance and Adaptability

New Generation of FPGA Based Distributed Accelerator Cards Offer High Performance and Adaptability
by Tom Simon on 12-05-2019 at 10:00 am

Achronix FPGA used on BittWare Accelerator Card

We have learned from nature that two characteristics are helpful for success, diversity and adaptability. The same has been shown to be true for computing systems. Things have come a long way from when CPU centric computing was the only choice. Much heavy lifting these days is done by GPUs, ASICs, and FPGAs, with CPUs in a support … Read More


Formal in the Field: Users are Getting More Sophisticated

Formal in the Field: Users are Getting More Sophisticated
by Bernard Murphy on 10-15-2019 at 5:00 am

Formal SIG 2019 meeting at Synopsys

Building on an old chestnut, if sufficiently advanced technology looks like magic, there are a number of technology users who are increasingly looking like magicians. Of course when it comes to formal, neither is magical, just very clever. The technology continues to advance and so do the users in their application of those methods.… 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


Mentor Highlights HLS Customer Use in Automotive Applications

Mentor Highlights HLS Customer Use in Automotive Applications
by Bernard Murphy on 07-30-2019 at 6:00 am

Catapult HLS

I’ve talked before about Mentor’s work in high-level synthesis (HLS) and machine learning (ML). An important advantage of HLS in these applications is its ability to very quickly adapt and optimize architecture and verify an implementation to an objective in a highly dynamic domain. Design for automotive applications – for … Read More


An evolution in FPGAs

An evolution in FPGAs
by Tom Simon on 05-24-2019 at 5:00 am

Why does it seem like current FPGA devices work very much like the original telephone systems with exchanges where workers connected calls using cords and plugs? Achronix thinks it is now time to jettison Switch Blocks and adopt a new approach. Their motivation is to improve the suitability of FPGAs to machine learning applications,… Read More