Building An AI Chip: Silicon Design And Advanced Packaging


AI has become a key driver for the semiconductor industry as it is applied to ever more aspects of daily life. Many startups and established vendors are designing AI chips to accelerate algorithms and yield the best results. AI designs are large and complex, requiring advanced process nodes and putting stress on every step of the development process. Multi-die, or chiplet-based, design is becom... » read more

When Semiconductor Materials Misbehave


Key Takeaways Material behavior in production depends on the process context that no development environment can fully replicate. In advanced packaging, the interactions that cross domain boundaries are increasingly where failures originate. The most accurate materials data is also the most commercially sensitive, leaving simulation models calibrated against generic inputs rather tha... » read more

Chip Industry Week In Review


Deals Marvell acquired Polariton Technologies, a Swiss developer of plasmonics-based silicon photonics devices. Onto Innovation is partnering with Rigaku, combining Onto’s analysis software with Rigaku’s CD-SAXS platform for advanced semiconductor process control. Onto also agreed to acquire a 27% stake in Rigaku for about $710M. Tesla plans to use Intel’s 14A process for its T... » read more

Can Edge AI Keep Up?


Key Takeaways: Model development is outpacing silicon design cycles, so edge AI architectures must prioritize adaptability. The required cadence for model updates is highly application-dependent and is closely tied to product lifetime and operational risk. Adaptability can conflict with power, performance, and area targets, so effective heterogeneous architectures and robust softwa... » read more

Blog Review: Apr. 22


In a podcast, Siemens EDA's Harry Foster and Vladislav Palfy chat about why coverage closure has become one of the biggest bottlenecks in modern verification and how a unified approach that combines planning, automation, and analytics helps teams break through coverage plateaus. Synopsys' Emily Gerken and Marc Swinnen consider the challenges of designing analog and mixed-signal circuits at a... » read more

Batteries Charge To The Edge


Long-awaited advances in battery chemistry and materials science are beginning to roll out, opening the door for higher capacity, faster charging, and much lower likelihood of thermal runaway. This is a high-stakes race, fueled by an insatiable demand for power everywhere from handheld devices to data centers. When Finland's Donut Lab claimed earlier this year that it had developed a solid-s... » read more

Chip Industry Week In Review


Acquisitions and business pivots Teradyne acquired Israel-based TestInsight, a semiconductor test provider with pattern conversion, validation, and virtual test capabilities. Credo plans to acquire DustPhotonics, a developer of silicon photonics PICs for optical transceivers. Molex plans to acquire Teramount, a provider of detachable, passive-alignment fiber-to-chip connectivity solu... » read more

Panel-Level Packaging’s Second Wave Meets Engineering Reality


Key Takeaways Panel-level packaging is arriving not because the engineering is ready, but because wafer-level economics are breaking down. Glass improves the warpage and dimensional stability problems of organic substrates but introduces a different class of failure modes that require materials solutions, not process adjustments. The central challenges of panel-level processing are m... » read more

Chiplet Standards Aim For Plug-n-Play


Key Takeaways Die-to-die chiplet standards are only the beginning. Many more standards are necessary for a chiplet marketplace. A number of such standards have either had initial versions released or are in progress. Existing work covers packaging, a system architecture, various design kits, a universal link layer, and updates to BoW. Today’s chiplets exist in silos. In a ... » read more

Automate And Speed Up TCAD Calibration With Expert Modules And ML Calibration Accelerator


Increasing complexity in semiconductor manufacturing has pushed the time to market and R&D costs significantly higher. In the world of AI, there is increased focus on efficiency to help address these issues simultaneously. Wafer-based learning, which is an iterative and linear process, is a key contributor to the increased semiconductor development time and cost. Technology computer-aided d... » read more

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