tag: machine learning

Moving Intelligence To The Edge
By Ed Sperling - 05 Apr, 2022 - Comments: 0

The buildout of the edge is driving a slew of new challenges and opportunities across the chip industry. Sailesh Chittipeddi, executive vice president at Renesas Electronics America, talks about the shift toward more AI-centric workloads rather than CPU-centric, why embedded computing is becoming the foundation of all intelligences, and the importance of software, security, and user experience ... » read more

Exploring far-from-equilibrium ultrafast polarization control in ferroelectric oxides with excited-state neural network quantum molecular dynamics
By Technical Paper Link - 01 Apr, 2022 - Comments: 0

New academic paper out of USC Viterbi School of Engineering: Abstract "Ferroelectric materials exhibit a rich range of complex polar topologies, but their study under far-from-equilibrium optical excitation has been largely unexplored because of the difficulty in modeling the multiple spatiotemporal scales involved quantum-mechanically. To study optical excitation at spatiotemporal scales w... » read more

An adaptive synaptic array using Fowler–Nordheim dynamic analog memory
By Technical Paper Link - 29 Mar, 2022 - Comments: 0

Abstract "In this paper we present an adaptive synaptic array that can be used to improve the energy-efficiency of training machine learning (ML) systems. The synaptic array comprises of an ensemble of analog memory elements, each of which is a micro-scale dynamical system in its own right, storing information in its temporal state trajectory. The state trajectories are then modulated by a sys... » read more

Week In Review: Manufacturing, Test
By Ed Sperling - 25 Mar, 2022 - Comments: 0

Worldwide fab equipment spending for front-end manufacturing is expected to hit $107 billion this year, an 18% year-over-year increase, according to SEMI’s latest World Fab Forecast report. “Crossing the $100 billion mark in spending on global fab equipment for the first time is a historic milestone for the semiconductor industry,” said Ajit Manocha, president and CEO of SEMI. Investme... » read more

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

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