We’re always looking for ways to leverage machine-learning (ML) in coverage refinement. Here is an intriguing approach proposed by Google Research. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and now Silvaco CTO) and I continue our series on research… Read More
Artificial Intelligence
Quantum Computing Trends
Quantum Computing is the area of study focused on developing computer technology based on the principles of quantum theory. Tens of billions of public and private capitals are being invested in Quantum technologies. Countries across the world have realized that quantum technologies can be a major disruptor of existing businesses,… Read More
Optimizing AI/ML Operations at the Edge
AI/ML functions are moving to the edge to save power and reduce latency. This enables local processing without the overhead of transmitting large volumes of data over power hungry and slow communication links to servers in the cloud. Of course, the cloud offers high performance and capacity for processing the workloads. Yet, … Read More
Webinar: From Glass Break Models to Person Detection Systems, Deploying Low-Power Edge AI for Smart Home Security
Moving deep learning from the cloud to the edge is the holy grail when it comes to deploying highly accurate, low-power applications. Market demand for edge AI continues to grow globally as new hardware and software solutions are now more readily available, enabling any sized company to easily implement deep learning solutions… Read More
Getting to Faster Closure through AI/ML, DVCon Keynote
Manish Pandey, VP R&D and Fellow at Synopsys, gave the keynote this year. His thesis is that given the relentless growth of system complexity, now amplified by multi-chiplet systems, we must move the verification efficiency needle significantly. In this world we need more than incremental advances in performance. We need… Read More
Dynamic Coherence Verification. Innovation in Verification
We know about formal methods for cache coherence state machines. What sorts of tests are possible using dynamic coherence verification? Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO) and I continue our series on research ideas. As always, feedback welcome.… Read More
Unlocking the Future with Robotic Precision and Human Creativity
From the perspective of all time for recorded human history, the last 300 years (a blink on that time scale) has seen incredible, life-changing and world-changing advances. Water and steam-driven machines first showed up in the 1700s. This is often called Industry 1.0. Powered assembly lines in the late 1800s became Industry … Read More
AI at the Edge No Longer Means Dumbed-Down AI
One aspect of received wisdom on AI has been that all the innovation starts in the big machine learning/training engines in the cloud. Some of that innovation might eventually migrate in a reduced/ limited form to the edge. In part this reflected the newness of the field. Perhaps also in part it reflected need for prepackaged one-size-fits-many… Read More
AI for EDA for AI
I’ve been noticing over the last few years that electronic design automation (EDA) vendors just love to talk about artificial intelligence (AI) and machine learning (ML), sometimes with deep learning (DL) and neural networks tossed in as well. It can get a bit confusing since these terms are used in two distinct contexts. The first… Read More
Ramping Up Software Ideas for Hardware Design
This is a topic in which I have a lot of interest, covered in a panel at this year’s DAC; Raúl Camposano chaired the session. I had earlier covered a keynote by Moshe Zalcberg at Europe DVCon late in 2020; he now reprises the topic. Given the incredible pace of innovation and scale in software development these days, I don’t see what we… Read More
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