Author's Latest Posts

Blog Review: Feb. 21

Siemens' John McMillan digs into physical verification maturity for high-density advanced packaging (HDAP) designs and major differences in the LVS verification flow compared to the well-established process for SoCs. Synopsys' Varun Shah identifies why a cloud adoption framework is key to getting the most out of deploying EDA tools in the cloud, including by ensuring that different types of ... » read more

Research Bits: Feb. 19

DNA assembly of 3D nanomaterials Scientists from Brookhaven National Laboratory, Columbia University, and Stony Brook University developed a method that uses DNA to instruct molecules to organize themselves into targeted 3D patterns and produce a wide variety of designed metallic and semiconductor 3D nanostructures. “We have been using DNA to program nanoscale materials for more than a de... » read more

Research Bits: Feb. 13

Fast phase-change memory Researchers from Stanford University, TSMC, National Institute of Standards and Technology (NIST), and University of Maryland developed a new phase-change memory for future AI and data-centric systems. It is based on GST467, an alloy of four parts germanium, six parts antimony, and seven parts tellurium, which is sandwiched between several other nanometer-thin material... » read more

Startup Funding: January 2024

Big rounds marked January, with three companies raising over $100 million. Quantum computing topped the list, with the company that resulted from the merger of Cambridge Quantum Computing and Honeywell's quantum division raking in the third-largest round for a quantum computing company ever. Another chart-topper was an advanced packaging company that began mass production in its first factor... » read more

Blog Review: Feb. 7

Synopsys' Ian Land, Kenneth Larsen, and Rob Aitken find that a new approach will be required to ensure that higher volume 3D heterogeneous integration (3DHI) designs can function reliably and successfully in aerospace, defense, and government systems. Siemens' John Golding provides a primer on the fundamental concepts related to signal integrity, including key topics such as transmission lin... » read more

Research Bits: Feb. 6

Laser printer for photonic circuits Researchers from the University of Washington and University of Maryland propose a faster, cheaper way to fabricate and reconfigure photonic integrated circuits. The method uses a laser writer to write, erase, and modify circuits into a thin film of phase-change material similar to what is used for recordable CDs and DVDs. The researcher say the method co... » read more

Blog Review: Jan. 31

Synopsys' William Ruby argues for a comprehensive energy-efficient design methodology for automotive ICs as today's vehicles demand ever more computing power to support electrification, communication, and processing of massive amounts of data. Cadence's Mellacheruvu Srikanth finds that verifying all the new features and enhancements across several generations of PCIe while maintaining backwa... » read more

Research Bits: Jan. 30

Etching tellurite glass Physicists from EPFL and Tokyo Tech propose a way to create photoconductive circuits, where the circuit is directly patterned onto a tellurite glass surface with femtosecond laser light. The exposure formed nanoscale tellurium and tellurium oxide crystals, both semiconducting materials. “Tellurium being semiconducting, based on this finding we wondered if it would ... » read more

Blog Review: Jan. 24

Siemens' John McMillan finds that while 3D-IC capabilities are ready for mainstream, mass adoption success depends on how easily, effectively, and efficiently a solution can be delivered and points to five workflow adoption focus areas. Cadence's Andre Baguenie shows how to easily convert a logic signal to an electrical value using Verilog-AMS and the transition filter. Synopsys' Chris Cl... » read more

Research Bits: Jan. 23

Memristor-based Bayesian neural network Researchers from CEA-Leti, CEA-List, and CNRS built a complete memristor-based Bayesian neural network implementation for classifying types of arrhythmia recordings with precise aleatoric and epistemic uncertainty. While Bayesian neural networks are useful for at sensory processing applications based on a small amount of noisy input data because they ... » read more

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