tag: ML

Digital Twins Find Their Footing In IC Manufacturing
By Laura Peters - 09 Jul, 2024 - Comments: 0

Momentum is building for digital twins in semiconductor manufacturing, tying together the various processes and steps to improve efficiency and quality, and to enable more flexibility in the fab and assembly house. The movement toward digital twins opens up a slew of opportunities, from building and equipping new fabs faster to speeding yield ramps by reducing the number of silicon-based tes... » read more

Navigating The Future Of EDA
By Anika Sunda - 27 Jun, 2024 - Comments: 0

The landscape of electronic design automation (EDA) is undergoing a monumental transformation. The catalysts? Artificial Intelligence (AI) and Machine Learning (ML). These technological marvels are not just reshaping how we approach design and verification in electronics; they are redefining the possibilities within the field. Our latest podcast episode delved deep into this topic, uncovering t... » read more

Applying Machine Learning To Accelerate TCAD Calibration
By Dwight Hunter - 20 Jun, 2024 - Comments: 0

TCAD models are the fundamental building blocks for the semiconductor industry. Whether it is a new process node or a new multi-billion dollar fab, accurate TCAD models must be developed and calibrated before they can be deployed in technology development. While TCAD models have been around for (many) decades, their complexity is growing exponentially, as is the demands placed on the R&D en... » read more

Precise Control Needed For Copper Plating And CMP
By Anne Meixner - 20 Jun, 2024 - Comments: 0

Chipmakers are relying on machine learning for electroplating and wafer cleaning at leading-edge process nodes, augmenting traditional fault detection/classification and statistical process control in order to extend the usefulness of copper interconnects. Copper is well understood and easy to work with, but it is running out of steam. At 5nm and below, copper plating tools are struggling to... » read more

AI: Great, But Somehow Still Not Very Good
By Charlie Parker - 20 Jun, 2024 - Comments: 0

In an invited presentation at CS Mantech 2024, Charlie Parker, senior machine learning engineer at Tignis, provides context for the AI hype cycle with a high-level overview of machine learning concepts, then explores how the technology fits into the fab, from inventory management to institutional knowledge capture, but warns that it is worth being aware of the ways in which machine learning mod... » read more

IC Industry’s Growing Role In Sustainability
By Ann Mutschler - 17 Jun, 2024 - Comments: 1

The massive power needs of AI systems are putting a spotlight on sustainability in the semiconductor ecosystem. The chip industry needs to be able to produce more efficient and lower-power semiconductors. But demands for increased processing speed are rising with the widespread use of large language models and the overall increase in the amount of data that needs to be processed. Gartner estima... » read more

KANs Explode!
By Steve Roddy - 13 Jun, 2024 - Comments: 0

In late April 2024, a novel AI research paper was published by researchers from MIT and CalTech proposing a fundamentally new approach to machine learning networks – the Kolmogorov Arnold Network – or KAN. In the six weeks since its publication, the AI research field is ablaze with excitement and speculation that KANs might be a breakthrough that dramatically alters the trajectory of AI mod... » read more

Opportunities Grow For GPU Acceleration
By Gregory Haley - 05 Jun, 2024 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss the impact of GPU acceleration on mask design and production and other process technologies, with Aki Fujimura, CEO of D2S; Youping Zhang, head of ASML Brion; Yalin Xiong, senior vice president and general manager of the BBP and reticle products division at KLA; and Kostas Adam, vice president of engineering at Synopsys. W... » read more

Chip Design Digs Deeper Into AI
By Ann Mutschler - 03 Jun, 2024 - Comments: 0

Growing demand for blazing fast and extremely dense multi-chiplet systems are pushing chip design deeper into AI, which increasingly is viewed as the best solution for sifting through scores of possible configurations, constraints, and variables in the least amount of time. This shift has broad implications for the future of chip design. In the past, collaborations typically involved the chi... » read more

Using Predictive Maintenance To Boost IC Manufacturing Efficiency
By Laura Peters - 14 May, 2024 - Comments: 0

Predicting exactly how and when a process tool is going to fail is a complex task, but it's getting a tad easier with the rollout of smart sensors, standard interfaces, and advanced data analytics. The potential benefits of predictive maintenance are enormous. Higher tool uptime correlates with greater fab efficiency and lower operating costs, so engineers are pursuing multiple routes to boo... » read more

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