AI Benchmarks Are Broken


Artificial Intelligence (AI) is shaping up to be one of the most revolutionary technologies of our time. By now you’ve probably heard that AI’s impact will transform entire industries, from healthcare to finance to entertainment, delivering us richer products, streamlined experiences, and augment human productivity, creativity, and leisure. Even non-technologists are getting a glimpse of... » read more

A Hierarchical And Tractable Mixed-Signal Verification Methodology For First-Generation Analog AI Processors


Artificial intelligence (AI) is now the key driving force behind advances in information technology, big data and the internet of things (IoT). It is a technology that is developing at a rapid pace, particularly when it comes to the field of deep learning. Researchers are continually creating new variants of deep learning that expand the capabilities of machine learning. But building systems th... » read more

Test Challenges Mount As Demands For Reliability Increase


An emphasis of improving semiconductor quality is beginning to spread well beyond just data centers and automotive applications, where ICs play a role in mission- and safety-critical applications. But this focus on improved reliability is ratcheting up pressure throughout the test community, from lab to fab and into the field, in products where transistor density continues to grow — and wh... » read more

Compiler Optimization Made Easy


In a previous blog post, we discussed the benefits of using automation to maximize the performance of a system. One use case I mentioned was compiler flag mining, and the fact that performance is available beyond the standard optimization flags provided by most compilers. Getting to this untapped performance is a difficult problem to solve, but fortunately there is an easy way. A universe of o... » read more

AI: Engineering Tool Or Threat To Jobs?


Semiconductor Engineering sat down to talk about using AI for designing and testing complex chips with Michael Jackson, corporate vice president for R&D at Cadence; Joel Sumner, vice president of semiconductor and electronics engineering at National Instruments; Grace Yu, product and engineering manager at Meta; David Pan, professor in the Department of Electrical and Computer Engineering a... » read more

Beyond Human Reach: Meeting Design Targets Faster With AI-Driven Optimization


The implementation flow for semiconductor devices is all about optimizing for power, performance, area (PPA), or some combination of these attributes. The history of this flow in electronic design automation (EDA) tools is all about adding more automation, tightening iterative loops, and reducing the number of iterations. The goal is converging to the PPA targets faster while using fewer resour... » read more

Safety, Security, And Reliability Of AI In Autos


Experts at the Table: Semiconductor Engineering sat down to talk about security, aging, and safety in automotive AI systems, with Geoff Tate, CEO of Flex Logix; Veerbhan Kheterpal, CEO of Quadric; Steve Teig, CEO of Perceive; and Kurt Busch, CEO of Syntiant. What follows are excerpts of that conversation, which was held in front of a live audience at DesignCon. Part one of this discussion is he... » read more

Review of Tools & Techniques for DL Edge Inference


A new technical paper titled "Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review" was published in "Proceedings of the IEEE" by researchers at University of Missouri and Texas Tech University. Abstract: Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted in breakthroughs in many areas. However, deploying thes... » read more

AI’s Impact In Automobiles Remains Uncertain


Experts at the Table: Semiconductor Engineering sat down to talk about software updates in cars, where AI makes sense, and why there's a growing sense of optimism, with Geoff Tate, CEO of Flex Logix; Veerbhan Kheterpal, CEO of Quadric; Steve Teig, CEO of Perceive; and Kurt Busch, CEO of Syntiant. What follows are excerpts of that conversation, which were held in front of a live audience at Desi... » read more

New Method Improves Machine Learning Models’ Reliability, With Less Computing Resources (MIT, U. of Florida, IBM Watson)


A new technical paper titled "Post-hoc Uncertainty Learning using a Dirichlet Meta-Model" was published (preprint) by researchers at MIT, University of Florida, and MIT-IBM Watson AI Lab (IBM Research). The work demonstrates how to quantify the level of certainty in its predictions, while using less compute resources. “Uncertainty quantification is essential for both developers and users o... » read more

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