Some amazing hardware is being designed to accelerate AI/ML, most of which features large numbers of MAC units. Given that MAC units are like the lego blocks of digital math, they are also useful for a number of other applications. System designers are waking up to the idea of repurposing AI accelerators for DSP functions such as … Read More
Artificial Intelligence
Accelerating Edge Inference with Flex Logix’s InferX X1
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
How does TensorFlow Lite on Tensilica HiFi DSP IP Sound?
In all the hubbub about AI/ML, it’s easy to see why visual ML gets more attention. It’s got appeal because of applications such as autonomous driving. Because of this it’s easy to overlook the importance of audio ML. I own a Tesla and putting it into autopilot is very cool, but even it has voice recognition built in as an important feature… Read More
Wave Computing and MIPS Wave Goodbye
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
Cadence – Defining a Roadmap to the Future
Cadence recently published a position paper that details a set of enabling technologies that will be needed for product design going forward. Entitled Intelligent System Design, the piece describes the changing landscape of system design and the requirements for success. Cadence has built a branded approach to address these… Read More
Artificial Intelligence in Micro-Watts: How to Make TinyML a Reality
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
Linley Spring Processor Conference Kicks Off – Virtually
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
Mentor Masterclass on ML SoC Design
I was scheduled to attend the Mentor tutorial at DVCon this year. Then coronavirus hit, two big sponsors dropped out and the schedule was shortened to three days. Mentor’s tutorial had to be moved to Wednesday and, as luck would have it, I already had commitments on that day. Mentor kindly sent me the slides and audio from the meeting… Read More
Cadence Digital Full Flow Optimized to Deliver Improved Quality of Results with Up to 3X Faster Throughput
Artificial intelligence (AI) and machine learning (ML) are hot topics. Beyond the impact these technologies are having on the world around us, they are also having impact on the semiconductor and EDA ecosystem. I posted a blog last week that discussed how Cadence views AI/ML, both from a tool and ecosystem perspective. The is one… Read More
Machine Learning for EDA – Inside, Outside and Everywhere Else
Artificial intelligence (AI) is everywhere. The rise of the machines is upon us in case you haven’t noticed. Machine learning (ML) and its associated inference abilities promise to revolutionize everything from driving your car to making breakfast. We hear a lot about the macro, end-product impact of this technology, but there… Read More


EDA Has a Value Capture Problem — An Outsider’s View