tag: ML

Thermal-Mechanical Optimization of 2.5D Flip-Chip Packages With Glass and Silicon Interposers (Univ. of Ottawa)
By Technical Paper Link - 06 Jan, 2026 - Comments: 0

A new technical paper titled "Thermo-mechanical co-design of 2.5D flip-chip packages with silicon and glass interposers via finite element analysis and machine learning" was published by researchers at University of Ottawa. Abstract "Advanced 2.5D flip-chip packages with silicon/glass interposers may pose tightly coupled thermo-mechanical trade-offs. This work presents a simulation-driven, ... » read more

Data-Centric ML Compiler For PIM (U. of Toronto, Barcelona Supercomputing Center, ETH Zurich, Max Planck)
By Technical Paper Link - 19 Dec, 2025 - Comments: 0

A new technical paper titled "A Tensor Compiler for Processing-In-Memory Architectures" was published by researchers at University of Toronto, Barcelona Supercomputing Center, ETH Zurich, and the Max Planck Institute for Software Systems. Abstract "Processing-In-Memory (PIM) devices integrated with high-performance Host processors (e.g., GPUs) can accelerate memory-intensive kernels in Ma... » read more

Benefits And Limits Of Using ML For Materials Discovery
By Katherine Derbyshire - 18 Dec, 2025 - Comments: 0

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development. Whether the goal is to identify new applications for known materials or to design new molecules for a particular task, these tools help materials scientists find correlations in large data libraries. Still, machine learning tools are not magic. “Software tools are only as... » read more

AI With Open And Scaled Data Sharing in IC Manufacturing (NIST)
By Technical Paper Link - 02 Dec, 2025 - Comments: 2

A new workshop report titled "Artificial Intelligence with Open and Scaled Data Sharing in Semiconductor Manufacturing" was published by NIST. Abstract "The Workshop sponsored by the National Science Foundation (NSF) (NSF award 2334590, "Artificial Intelligence with Open and Scaled Data Sharing in the Semiconductor Industry") and supported by the National Institute of Standards and Techno... » read more

Machine Learning Tools Accelerate Materials Discovery
By Katherine Derbyshire - 20 Nov, 2025 - Comments: 0

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

Advanced Process Control In Semiconductor Manufacturing
By Ed Sperling - 14 Nov, 2025 - Comments: 0

Fifth in a seven-part series: Advanced process control for semiconductor wafers is evolving in ways that can significantly improve yield and reduce scrap. As dimensions shrink, the need to improve manufacturing processes and reduce variability requires more precision. "Classic" APC was a step in the right direction, identifying problems in a process chamber, for example, and automating adjustme... » read more

Using AI/ML To Find And Correlate IC Test Data
By Ed Sperling - 15 Oct, 2025 - Comments: 0

What causes low yield in wafers? Usually it's due to design or process changes, but sometimes yield issues occur even if there haven't been any changes from one manufacturing lot to the next. Finding the cause requires some sleuthing, and the best approach for pinpointing problems is to mine design, process, and manufacturing data, and to correlate that data by date and time, by which equipment... » read more

What Does Semiconductor Disruption Look Like?
By Brian Bailey - 25 Sep, 2025 - Comments: 2

When conducting interviews for my article on the incorporation of AI within EDA tools, Anand Thiruvengadam, senior director and head of AI product management at Synopsys, said, "AI has the potential to transform how customers do chip design. The entire EDA flow can be disrupted with AI." He is not alone in making this kind of statement. Each year, I do a predictions piece, and I ask about how A... » read more

AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning
By Yiao Li - 28 Aug, 2025 - Comments: 1

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure reliable circuit simulation and design. Correspondingly, these accuracy requirements raise demands on the accuracy and efficiency of device modeling. Modern device models often involve hundreds o... » read more

AI, From A To Z
By Ed Sperling - 15 Aug, 2025 - Comments: 0

First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

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