Chip Industry Week in Review


Major Deals: Taiwan-based UMC is exploring possible collaboration with Polar Semiconductor for high-volume production of 8-inch wafers at Polar’s expanded Minnesota fab, a move that could provide domestic manufacturing capacity for automotive, data center, consumer, aerospace, and defense customers. Marvell will acquire Celestial AI for $3.25B, adding photonic fabric technology for o... » read more

Small Language Models Create New Security Risks


The rollout of edge AI is creating new security risks due to a mix of small language models (SLMs), their integration into increasingly complex hardware, and the behavior and interactions of both over time. AI data centers still garner the most attention due to massive investments and an ongoing flood of deals and acquisitions, but the edge is quietly starting to take shape for several reaso... » read more

Physical AI Takes Functional Safety Cues From Automotive


Robots are becoming smarter, more capable, and more pervasive, setting the stage for a whole new round of growth that will touch nearly every part of the semiconductor and software industries for decades to come. Robots are at the core of physical AI, a broad segment of edge AI systems that interact with the world through artificial intelligence and sensors. This includes everything from hum... » read more

Harnessing Silicon Lifecycle Management For Chip Security


Silicon lifecycle management is starting to be used in ways that extend well beyond its original mission of ensuring a chip functions to spec throughout its expected lifetime. While tracking aging effects and component failures are still important, the technology also is being deployed to proactively monitor, authenticate, and respond to potential threats in real-time. In fact, not applying ... » read more

Blog Review: Dec. 3


Cadence's Reela Samuel notes that as multi-die integration becomes the new engine of semiconductor performance, the decision between 2.5D and 3D-IC architectures shapes a design's achievable bandwidth, energy efficiency, thermal limits, system size, and even program schedules. Synopsys' Thomas Andersen suggests that the deployment of physical AI will require the fusion of advanced electronic... » read more

SRAM PUF: A Revolutionary Approach to Cryptographic Key Protection


Cryptographic keys are the cornerstone of secure digital systems, enabling encryption, authentication, and data integrity. However, securely storing these keys on-chip presents significant challenges. Traditional methods, such as storing keys in one-time programmable, non-volatile memory, are vulnerable to physical attacks, environmental variations, and lifecycle management issues. Physical Unc... » read more

Optimizing AI Workloads For Edge Computing


Experts At The Table: Semiconductor Engineering gathered a group of experts to discuss how some AI workloads are better suited for on-device processing to achieve consistent performance, avoid network connectivity issues, reduce cloud computing costs, and ensure privacy. The panel included Frank Ferro, group director in the Silicon Solutions Group at Cadence; Eduardo Montanez, vice president an... » read more

Chip Industry Week In Review


Breaking news: Nvidia and Synopsys announced a multi-faceted, multi-year deal that includes everything from digital twins to CUDA programming, engineering, and marketing collaboration, and Nvidia's $2B purchase of Synopsys stock. [Updated 12/1] Memory news: Micron is building a $9.6B HBM facility in the city of Higashi-Hiroshima Japan, reports Nikkei. China's ChangXin Memory Technol... » read more

Blog Review: Nov. 26


Cadence's Rajneesh Chauhan explains CXL's low power state, L0p, which maintains partial lane activity for efficient power management without compromising performance, and how comprehensive verification can help ensure reliable implementation. Siemens' John Ferguson provides a brief history of design rule checking, major advancements over the years, and why introducing it in earlier design st... » read more

AI Plays Multiple Roles Within EDA


AI's infusion into our world may seem sudden and unexpected, but EDA has been quietly adopting it for more than a decade. What's changed is that it's now becoming more visible, thanks to increasingly powerful large language models (LLMs) and the need to apply them to increasingly challenging multi-physics problems. Two fundamental shifts underlie AI's increasing prominence. First, heat is be... » read more

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