Chip Industry Week In Review


By Adam Kovac, Gregory Haley, and Liz Allan. Cadence plans to acquire BETA CAE Systems for $1.24 billion, the latest volley in a race to sell multi-physics simulation and analysis across a broad set of customers with deep pockets. Cadence said the deal opens the door to structural analysis for the automotive, aerospace, industrial, and health care sectors. Under the terms of the agreement, 6... » read more

Research Bits: Dec. 20


Patch tracks blood in deep tissue A skin-worn photoacoustic patch developed by a research team at the University of California San Diego is equipped with arrays of laser diodes and piezoelectric transducers to detect biomolecules in deep tissues, which usually would require a magnetic resonance imaging (MRI) and X-ray-computed tomography. The patch may help doctors tract hemoglobin in real tim... » read more

Technical Paper Roundup: Sept 27


New technical papers added to Semiconductor Engineering’s library this week. [table id=53 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit f... » read more

Hardware Implementation Of A Random Gumber Generator On A FPGA


A new research paper titled "FPGA Random Number Generator" was published by a researcher at Johns Hopkins University. According to the paper's abstract: "This paper offers a proof-of-concept for creating a verilog-based hardware design that utilizes random measurement and scrambling algorithms to generate 32-bit random synchronously with a single clock cycle on a field-programmable-gate-arr... » read more

It’s Eternal Spring For AI


The field of Artificial Intelligence (AI) has had many ups and downs largely due to unrealistic expectations created by everyone involved including researchers, sponsors, developers, and even consumers. The “reemergence” of AI has lot to do with recent developments in supporting technologies and fields such as sensors, computing at macro and micro scales, communication networks and progre... » read more

COVID-19 Tech Bits


Tech companies, consortiums and universities are jumping in to help fight COVID-19, deploying everything from massive computing capabilities to developing new technologies that can protect medical workers and first responders. Nearly all of these have ramped up over the past several weeks, as the tech world begins to take on a global challenge to combat the deadly virus. Compute resources... » read more

Thomas Dolby’s Very Different View Of Progress


Thomas Dolby’s hit songs “She Blinded Me with Science” and “Hyperactive!” catapulted him to international fame in the early '80s as a pioneer of New Wave and Electronica by combining a love for invention with a passion for music. The result defined an era of revolutionary music. As record company politics began to overshadow the joy of performing, Dolby turned his attention to Holl... » read more

Power/Performance Bits: Aug. 20


Six-angstrom waveguide Engineers at the University of California San Diego, City University of New York, and Johns Hopkins University created the thinnest optical waveguide yet. At only three atoms thick, the team says the waveguide serves as a proof of concept for scaling down optical devices. The waveguide consists of a tungsten disulfide monolayer (made up of one layer of tungsten atoms ... » read more

Week in Review: IoT, Security, Auto


Internet of Things Paris-based Parrot Drones and five other companies were selected by the Pentagon’s Defense Innovation Unit and the U.S. Army to adapt off-the-shelf commercial drones for combat applications as part of the Army’s Short Range Reconnaissance program. SRR seeks to develop unmanned aerial vehicles that have a flight time of 30 minutes, a range of three kilometers (nearly two ... » read more

Power/Performance Bits: April 8


Predicting battery life Researchers at Stanford University, MIT, and Toyota Research Institute developed a machine learning model that can predict how long a lithium-ion battery can be expected to perform. The researchers' model was trained on a few hundred million data points of batteries charging and discharging. The dataset consists of 124 commercial lithium iron phosphate/graphite cells... » read more

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