tag: data models

Improving ML-Based Device Modeling Using Variational Autoencoder Techniques
By Technical Paper Link - 27 Sep, 2023 - Comments: 0

A technical paper titled “Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques” was published by researchers at Commonwealth Scientific and Industrial Research Organisation (CSIRO), Peking University, National University of Singapore, and University of New South Wales. Abstract: "The semiconductors industry benefits greatly from the integ... » read more

Making The Most Of Data Lakes
By Anne Meixner - 09 Aug, 2022 - Comments: 0

Having all the semiconductor data available is increasingly necessary for improving manufacturability, yield, and ultimately the reliability of end devices. But without sufficient knowledge of relationships between data from different processes and computationally efficient data structures, the value of any data is significantly reduced. In the semiconductor industry, reducing waste, decreas... » read more

Finding And Applying Domain Expertise In IC Analytics
By Anne Meixner - 12 Apr, 2022 - Comments: 0

Behind PowerPoint slides depicting the data inputs and outputs of a data analytics platform belies the complexity, effort, and expertise that improve fab yield. With the tsunami of data collected for semiconductor devices, fabs need engineers with domain expertise to effectively manage the data and to correctly learn from the data. Naively analyzing a data set can lead to an uninteresting an... » read more

The Automation Of AI
By Brian Bailey - 28 Mar, 2019 - Comments: 0

Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO ... » read more

What we know after twelve years developing and deploying test data analytics solutions
By Technical Paper Link - 31 Dec, 2016 - Comments: 0

Abstract: Since 2004, Texas Instruments and Portland State University have collaborated to develop and deploy test data analytical methods for use in a variety of applications, including quality screening, burn-in minimization, high cost test replacement and/or removal, and operations monitoring. In this paper, key findings amassed during this time are summarized. Find the technical paper h... » read more

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