Looking Beyond TOPS/W: How To Really Compare NPU Performance


There is a lot more to understanding the true capabilities of an AI engine beyond TOPS per watt. A rather arbitrary measure of the number of operations of an engine per unit of power, the TOPS/W metric completely misses the point that a single operation on one engine may accomplish more useful work than a multitude of operations on another engine. In any case, TOPS/W is by no means the only spe... » read more

How AI Drives Faster Verification Coverage And Debug For First-Time-Right Silicon


By Taruna Reddy and Robert Ruiz These days, the question is less about what AI can do and more about what it can’t do. From talk-of-the-town chatbots like ChatGPT to self-driving cars, AI is becoming pervasive in our everyday lives. Even industries where it was perhaps an unlikely fit, like chip design, are benefiting from greater intelligence. What if one of the most laborious, time-co... » 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

Getting Smarter About Tool Maintenance


Chipmakers have begun to shift to predictive maintenance for process tools, but the hefty investment in analytics and engineering efforts means it will take some time for smart maintenance to become a widespread practice. Semiconductor manufacturers need to maintain a diverse set of equipment to process the flow of wafers, dies, packaged parts, and boards running through factories. OSAT and ... » read more

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

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