Power/Performance Bits: Aug. 25


AI architecture optimization Researchers at Rice University, Stanford University, University of California Santa Barbara, and Texas A&M University proposed two complementary methods for optimizing data-centric processing. The first, called TIMELY, is an architecture developed for “processing-in-memory” (PIM). A promising PIM platform is resistive random access memory, or ReRAM. Whil... » read more

What’s Next For Semis?


It’s been a turbulent year in the semiconductor industry. 2020 was supposed to be a strong year. Then, the coronavirus outbreak hit. Suddenly, a large percentage of countries implemented various measures to mitigate the outbreak, such as stay-at-home orders as well as business and store closures. Economic turmoil and job losses soon followed, not to mention the human tragedy involved. M... » read more

Monitoring Chips After Manufacturing


New regulations and variability of advanced process nodes are forcing chip designers to insert additional capabilities in silicon to help with comprehension, debug, analytics, safety, security, and design optimization. The impact of this will be far-reaching as the industry discusses what capabilities can be shared between these divergent tasks, the amount of silicon area to dedicate to it, ... » read more

The Challenge Of Keeping AI Systems Current


Semiconductor Engineering sat down to discuss AI and its move to the edge with Steven Woo, vice president of enterprise solutions technology and distinguished inventor at Rambus; Kris Ardis, executive director at Maxim Integrated; Steve Roddy, vice president of Arm's Products Learning Group; and Vinay Mehta, inference technical marketing manager at Flex Logix. What follows are excerpts of that ... » read more

The Emergence Of Hardware As A Key Enabler For The Age Of Artificial Intelligence


Over the past few decades, software has been the engine of innovation for countless applications. From PCs to mobile phones, well-defined hardware platforms and instruction set architectures (ISA) have enabled many important advancements across vertical markets. The emergence of abundant-data computing is changing the software-hardware balance in a dramatic way. Diverse AI applications in fa... » read more

Scaling AI/ML Training Performance With HBM2E Memory


In my April SemiEngineering Low Power-High Performance blog, I wrote: “Today, AI/ML neural network training models can exceed 10 billion parameters, soon it will be over 100 billion.” “Soon” didn’t take long to arrive. At the end of May, OpenAI unveiled a new 175-billion parameter GPT-3 language model. This represented a more that 100X jump over the size of GPT-2’s 1.5 billion param... » read more

Semiconductors And The Climate Curve


On July 22 I participated in a panel at the virtual SEMICON West conference called “Bending the Climate Curve: Enabling Sustainable Growth of Big Data, AI, and Cloud Computing.” Virtual conferences are mandatory these days, but give a different experience than physical ones. They are very good at disseminating information and are reasonably effective at networking. But, in my experience... » read more

Power And Performance Optimization At 7/5/3nm


Semiconductor Engineering sat down to discuss power optimization with Oliver King, CTO at Moortec; João Geada, chief technologist at Ansys; Dino Toffolon, senior vice president of engineering at Synopsys; Bryan Bowyer, director of engineering at Mentor, a Siemens Business; Kiran Burli, senior director of marketing for Arm's Physical Design Group; Kam Kittrell, senior product management group d... » read more

Chiplet Reliability Challenges Ahead


Assembling chips using LEGO-like hard IP is finally beginning to take root, more than two decades after it was first proposed, holding the promise of faster time to market with predictable results and higher yield. But as these systems of chips begin showing up in mission-critical and safety-critical applications, ensuring reliability is proving to be stubbornly difficult. The main driver fo... » read more

The Very Long Road To Autonomous Vehicles


It may be a long wait before fully autonomous vehicles hit the road. Even semi-autonomous vehicles aren't doing so well. The American Automobile Association drove 4,000 miles in cars equipped with active driver assistance, averaging problems every 8 miles. AAA cited a host of problems, including driving too close to other cars or guardrails, aggressive braking, and automated steering that wo... » read more

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