tag: machine learning

Improving Machine Learning-Based Modeling of Semiconductor Devices by Data Self-Augmentation
By Technical Paper Link - 24 Mar, 2022 - Comments: 0

Abstract: "In the electronics industry, introducing Machine Learning (ML)-based techniques can enhance Technology Computer-Aided Design (TCAD) methods. However, the performance of ML models is highly dependent on their training datasets. Particularly in the semiconductor industry, given the fact that the fabrication process of semiconductor devices is complicated and expensive, it is of grea... » read more

Autonomous Design Automation: How Far Are We?
By Frank Schirrmeister - 24 Mar, 2022 - Comments: 0

The year is 2009, during the Design Automation Conference (DAC) at a press dinner in a posh little restaurant in San Francisco’s Civic Center. About two glasses of red wine in, one of the journalists challenges the table: “So, how far away are we from the black box that we feed with our design requirements and it produces the design that we send to the foundry?” We discussed all the indus... » read more

Cataloging IP In The Enterprise
By Ed Sperling - 22 Mar, 2022 - Comments: 0

Many companies have no way of documenting where IP they license is actually used, which version of that IP is being utilized, and whether that license extends to other projects or even to their customers. Pedro Pires, applications engineer at ClioSoft, looks at how IP currently is cataloged, why it’s been so difficult to do this in the past, and how AI can be used to speed up and simplify thi... » read more

A Framework For Ultra Low-Power Hardware Accelerators Using NNs For Embedded Time Series Classification
By Fraunhofer IIS/EAS - 09 Mar, 2022 - Comments: 0

In embedded applications that use neural networks (NNs) for classification tasks, it is important to not only minimize the power consumption of the NN calculation, but of the whole system. Optimization approaches for individual parts exist, such as quantization of the NN or analog calculation of arithmetic operations. However, there is no holistic approach for a complete embedded system design ... » read more

Machine Learning Showing Up As Silicon IP
By Bryon Moyer - 03 Mar, 2022 - Comments: 0

New machine-learning (ML) architectures continue to appear. Up to now, each new offering has been implemented in a chip for sale, to be placed alongside host processors, memory, and other chips on an accelerator board. But over time, more of this technology could be sold as IP that can be integrated into a system-on-chip (SoC). That trend is evident at recent conferences, where an increasing... » read more

Why RISC-V Is Succeeding
By Brian Bailey - 24 Feb, 2022 - Comments: 5

There is no disputing the excitement surround the introduction of the RISC-V processor architecture. Yet while many have called it a harbinger of a much broader open-source hardware movement, the reasons behind its success are not obvious, and the implications for an expansion of more open-source cores is far from certain. “The adoption of RISC-V as the preferred architecture for many sili... » read more

Addressing Library Characterization And Verification Challenges Using ML
By Siemens EDA - 23 Feb, 2022 - Comments: 0

At advanced process nodes, Liberty or library (.lib) requirements are more demanding due to design complexities, increased number of corners required for timing signoff, and the need for statistical variation modeling. This results in an increase in size, complexity, and the number of .lib characterizations. Validation and verification of these complex and large .lib files is a challenging task... » read more

Technology Advances, Shortages Seen For Wire Bonders
By Mark LaPedus - 17 Feb, 2022 - Comments: 2

A surge in demand for IC packages is causing long lead times for wire bonders, which are used to assemble three-fourths of the world’s packages. The wire bonder market doubled last year, alongside advanced packaging’s rise. Wirebonding is an older technology that typically flies under the radar. Still, packaging houses have multitudes of these key tools that help assemble many — but no... » read more

Improving PPA In Complex Designs With AI
By John Koon - 14 Feb, 2022 - Comments: 0

The goal of chip design always has been to optimize power, performance, and area (PPA), but results can vary greatly even with the best tools and highly experienced engineering teams. Optimizing PPA involves a growing number of tradeoffs that can vary by application, by availability of IP and other components, as well as the familiarity of engineers with different tools and methodologies. Fo... » read more

Enhancing Datasets For Artificial Intelligence Through Model-Based Methods
By Dirk Mayer - 10 Feb, 2022 - Comments: 0

By Dirk Mayer and Ulf Wetzker Industrial plants and processes are now digitized and networked, and AI can be used to evaluate the data generated by those facilities to increase productivity and quality. Machine learning (ML) methods can be applied to: Product quality classification in complex production processes. Condition monitoring of technical systems, which is used, for examp... » read more

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