What’s Missing In Test


Experts at the Table: Semiconductor Engineering sat down to discuss how functional test content is brought up at first silicon, and the balance between ATE and system-level testing, with Klaus-Dieter Hilliges, V93000 platform extension manager at Advantest Europe; Robert Cavagnaro, fellow in the Design Engineering Group at Intel (responsible for manufacturing and test strategy of data center... » read more

When To Expect Domain-Specific AI Chips


The chip industry is moving toward domain-specific computation, while artificial intelligence (AI) is moving in the opposite direction, creating a gap that could force significant changes in how chips and systems are architected in the future. Behind this split is the amount of time it takes to design hardware and software. In the 18 months since ChatGPT was launched on the world, there has ... » read more

Probing Attacks Against Chiplets


A technical paper titled “Evaluating Vulnerability of Chiplet-Based Systems to Contactless Probing Techniques” was published by researchers at University of Massachusetts and Worcester Polytechnic Institute. Abstract: "Driven by a need for ever increasing chip performance and inclusion of innovative features, a growing number of semiconductor companies are opting for all-inclusive System-... » read more

Power-Aware Revolution In Automated Test For ICs


As semiconductor devices advance in complexity and sensitivity to power fluctuations, the integration of power-aware automatic test pattern generation (ATPG) is becoming indispensable for yield and the overall functionality of a chip. Unlike traditional ATPG, which generates test patterns solely to ensure device functionality, power-aware ATPG takes it a step further by meticulously consider... » read more

Adoption of Chiplet Technology in the Automotive Industry


A technical paper titled "Chiplets on Wheels: Review Paper on Holistic Chiplet Solutions for Autonomous Vehicles" was published by researchers at the Indian Institute of Technology, Madras. Abstract "On the advent of the slow death of Moore's law, the silicon industry is moving towards a new era of chiplets. The automotive industry is experiencing a profound transformation towards software-... » read more

Making Adaptive Test Work Better


One of the big challenges for IC test is making sense of mountains of data, a direct result of more features being packed onto a single die, or multiple chiplets being assembled into an advanced package. Collecting all that data through various agents and building models on the tester no longer makes sense for a couple reasons — there is too much data, and there are multiple customers using t... » read more

Chip Industry Week In Review


JEDEC and the Open Compute Project rolled out a new set of guidelines for standardizing chiplet characterization details, such as thermal properties, physical and mechanical requirements, and behavior specs. Those details have been a sticking point for commercial chiplets, because without them it's not possible to choose the best chiplet for a particular application or workload. The guidelines ... » read more

Will Chiplet Adoption Mimic IP Adoption?


If we look at the semiconductor industry expansion during the last 25 years, adoption of design IP in every application appears to be one of the major factors of success, with silicon technology incredible development by a x100 factor, from 250nm in 2018 to 3nm (if not 2nm) in 2023. We foresee the move to chiplet-based architecture to soon play the same role that SoC chip-based architecture and... » read more

Considerations to Successfully Integrate Chiplets in Designs


Chiplet integration is a promising approach to creating heterogeneous and complex system-on-chips (SoCs) with significant performance, power, scalability, flexibility, and cost benefits. However, chiplet integration also poses substantial design, verification, testing, and packaging challenges, requiring new standards and design methodologies. Electronic design automation (EDA) software and sim... » read more

Scheduling Multi-Model AI Workloads On Heterogeneous MCM Accelerators (UC Irvine)


A technical paper titled “SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators” was published by researchers at University of California Irvine. Abstract: "Emerging multi-model workloads with heavy models like recent large language models significantly increased the compute and memory demands on hardware. To address such increasing demands, designin... » read more

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