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

3DKs: Making Headway On Chiplet Standards


The chiplet model has been proven by the early adopters. Large companies that successfully developed chips at leading nodes have integrated multiple chiplets into systems, where the entire silicon cycle is performed in-house. But the industry’s long-term goal of a free and open chiplet marketplace, in which companies of any size can reap the rewards and economies of scale associated with mult... » 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

FPGAs Find New Workloads In The High-Speed AI Era


FPGAs are finding new applications in the age of artificial intelligence, high-speed wireless communications, medical and life science technology, and in complex chip architectures where they can improve the flow of data. Field-programmable gate arrays (FPGAs) enable designers to reprogram or reconfigure digital logic after the chips have been deployed, which is essential in the AI world, wher... » read more

The Real-World Impact Of Silicon Lifecycle Management On Chip Architectures


Silicon lifecycle management (SLM) is transforming chip architectures, empowering designers to build smarter, more resilient, and secure semiconductor devices by leveraging data from manufacturing to end of life in the field. That data can be used to improve future designs, reduce margin, and continuously optimize performance and power efficiency throughout a chip's lifetime. Moreover, under... » read more

New Panel Production Efforts Target Interposer Costs


The rising cost of increasingly large interposers is spurring renewed interest in panel-level manufacturing, which for years has hobbled along due to the massive and collective effort required by the chip industry to change formats. Several companies are developing their own processes, although there is currently no commercial production. And a new consortium called Joint3, spearheaded by Ja... » read more

Machine Learning Tools Accelerate Materials Discovery


Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven software tools that promise to accelerate all three. Many of the challenges facing the semiconductor manufacturing industry are fundamentally materials science problems. What metal has the lowest resi... » read more

The Thermal Trap: How Dielectrics Limit Device Performance


The spread of artificial intelligence is forcing an uncomfortable truth on semiconductor manufacturing. Thin films, which are essential for isolating signals and insulating different components and metal layers, are becoming heat traps as physical dimensions continue to shrink in chips used inside AI data centers. That, in turn, is limiting how fast these chips can process data and increasing t... » read more

The Future For Formal Verification


Experts at the table: Semiconductor Engineering sat down to discuss possible future directions for formal verification technology with Ashish Darbari, CEO for Axiomise; Jin Zhang, product management group director for the Verification Group at Cadence; Sean Safarpour, executive director for R&D at Synopsys; and Jeremy Levitt, principal engineer for Digital Verification Technology at Siemen... » read more

Edge AI Is Starting To Transform Industrial IoT


A slew of wireless and increasingly multi-modal sensors is being targeted at the Industrial Internet of Things (IIoT), setting the stage for significant improvements in efficiency, higher yield, and reduced downtime. Wired IIoT devices, such as smart energy meters and breakers, industrial network gateways, and environmental sensors already are well established in factory settings. They have ... » read more

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