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
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
There is No Easy Fix to AI Privacy Problems
Artificial intelligence – more specifically, the machine learning (ML) subset of AI – has a number of privacy problems.
Not only does ML require vast amounts of data for the training process, but the derived system is also provided with access to even greater volumes of data as part of the inference processing while in operation. … Read More
Trends in AI and Safety for Cars
The potential for AI in cars, whether for driver assistance or full autonomy, has been trumpeted everywhere and continues to grow. Within the car we have vision, radar and ultrasonic sensors to detect obstacles in front, behind and to the side of the car. Outside the car, V2x promises to share real-time information between vehicles… Read More
Mentor Helps Mythic Implement Analog Approach to AI
The entire field of Artificial Intelligence (AI) has resulted from what is called “first principles thinking”, where problems are re-examined using a complete reassessment of the underlying issues and potential solutions. It is a testament to how effective this can be that AI is being used for a rapidly expanding number of applications… Read More
Webinar – FPGA Native Block Floating Point for Optimizing AI/ML Workloads
Block floating point (BFP) has been around for a while but is just now starting to be seen as a very useful technique for performing machine learning operations. It’s worth pointing out up front that bfloat is not the same thing. BFP combines the efficiency of fixed point operations and also offers the dynamic range of full floating… Read More
Facing the Quantum Nature of EUV Lithography