Concurrent Test


Derek Wu, senior staff applications engineer at Advantest, looks at the need for doing multiple tests at the same time as chip designs become more complex, increasingly heterogeneous, and much more difficult to test at advanced nodes. https://youtu.be/-8inbjX_af0       __________________________________ See more tech talk videos here. » read more

Week in Review: IoT, Security, Auto


Internet of Things Automotive, health care, manufacturing, and the public sector could be transformed this year by Internet of Things technology, Bob Violino writes. Taqee Khaled, director of strategy at Nerdery, a digital business consultancy, predicts 2019 will see rapid evolution in enterprise IoT pilot initiatives and implementations. "This acceleration is due, in part, to advances in manu... » read more

Power/Performance Bits: Jan. 8


Ferrimagnetic memory Engineers at the National University of Singapore, Toyota Technological Institute, and Korea University propose a new type of spintronic memory that is 20 times more efficient and 10 times more stable than commercial ones. In spintronic devices, data is stored depending on up or down magnetic states. Current devices based on ferromagnets, however, suffer from a few issu... » read more

Top Tech Talks Of 2018


2018 shaped up to be a year of transition and inflection, sometimes in the same design. There were new opportunities in automotive, continued difficulties in scaling, and an explosion in AI and machine learning everywhere. Traffic numbers on stories give a snapshot of the most current trends, but with videos those trends are even more apparent because of the time invested in watching those v... » read more

System Bits: Dec. 26


Adding learning to computer vision UCLA’s Samueli School of Engineering and Stanford University are working on advanced computer vision technology, using artificial intelligence to help vision systems learn to identify faces, objects and other things on their own, without training by humans. The research team breaks up images into chunks they call “viewlets,” then they have the computer ... » read more

It’s All About The Data


The entire tech industry has changed in several fundamental ways over the past year due to the massive growth in data. Individually, those changes are significant. Taken together, those changes will have a massive impact on the chip industry for the foreseeable future. The obvious shift is the infusion of AI (and its subcategories, machine learning and deep learning) into different markets. ... » read more

Fundamental Shifts In 2018


What surprised the industry in 2018?  While business has been strong, markets are changing, product categories are shifting and clouds are forming on the horizon. As 2018 comes to a close, most companies are pretty happy with the way everything turned out. Business has been booming, new product categories developing, and profits are meeting or beating market expectations. "2018 was indeed a... » read more

Deep Learning Hardware: FPGA vs. GPU


FPGAs or GPUs, that is the question. Since the popularity of using machine learning algorithms to extract and process the information from raw data, it has been a race between FPGA and GPU vendors to offer a HW platform that runs computationally intensive machine learning algorithms fast and efficiently. As Deep Learning has driven most of the advanced machine learning applications, it is r... » read more

AI Market Ramps Everywhere


Artificial Intelligence (AI) has inspired the general populace, but its rapid rise over the past few years has given many people pause. From realistic concerns about robots taking over jobs to sci-fi scares about robots more intelligent than humans building ever smarter robots themselves, AI inspires plenty of angst. Within the technology industry, we have a better understanding about the pote... » read more

Improving Library Characterization with Machine Learning


Efficient and accurate library characterization is a critical step in full-chip or block-level design flows because it ensures that all library elements perform to specification under all intended operating conditions. However, traditional library characterization and validation have become increasingly expensive in terms of computation and engineering effort, due to complexity and the amount o... » read more

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