On The Reverse Breakdown Behavior Of GaAs PIN Diodes For High Power Applications


In the field of power electronics, the compound semiconductors gallium nitride and silicon carbide are dominating the market. Due to its beneficial properties, gallium arsenide is gaining more and more importance. The aim is to manufacture devices based on gallium arsenide for use in power electronics with comparable or better properties, but at lower costs. In this work, a first GaAs PIN diode... » read more

What’s The Difference Between An NPU And A GPNPU?


To understand the difference between an NPU (neural processing unit) and a GPNPU (general-purpose neural processing unit) let’s start with the NPU, a processing engine that accelerates machine learning (ML) workloads in System on Chip (SoC) designs. Click here to read more. » read more

Blog Review: Jan. 11


Cadence's Veena Parthan explains why in CFD, understanding the consequences of choices regarding the computational mesh is essential for generating high-fidelity simulation results. Synopsys' Chris Clark shares key considerations and questions to factor in when developing solutions for software-defined vehicles that must meet safety, security, reliability, and quality standards. Siemens E... » read more

Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU (Ecole Polytechnique Montreal, IBM, Mila, CMC)


A new technical paper titled "BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU" was written by researchers at Ecole Polytechnique Montreal, IBM, Mila and CMC Microsystems. It was accepted for publication in the 2023, 28th Asia and South Pacific Design Automation Conference (ASP-DAC 2023) in Japan. Abstract: "We present a DNN accelerator that allows inference at arbitr... » read more

Technique For Printing Electronic Circuits Onto Curved & Corrugated Surfaces Using Metal Nanowires (NC State)


A technical paper titled "Curvilinear soft electronics by micromolding of metal nanowires in capillaries" was published by researchers at North Carolina State University. “We’ve developed a technique that doesn’t require binding agents and that allows us to print on a variety of curvilinear surfaces,” says Yuxuan Liu, first author of the paper and a Ph.D. student at NC State in this ... » read more

FPGA-Based Prototyping Framework For Processing In DRAM (ETH Zurich & TOBB Univ.)


A technical paper titled "PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM" was published by researchers at ETH Zurich and TOBB University of Economics and Technology. Abstract "Processing-using-memory (PuM) techniques leverage the analog operation of memory cells to perform computation. Several recent works have demonstrated PuM techniques in off-the-shelf DRAM dev... » read more

Screening For Silent Data Errors


Engineers are beginning to understand the causes of silent data errors (SDEs) and the data center failures they cause, both of which can be reduced by increasing test coverage and boosting inspection on critical layers. Silent data errors are so named because if engineers don’t look for them, then they don’t know they exist. Unlike other kinds of faulty behaviors, these errors also can c... » read more

Metrology Options Increase As Device Needs Shift


Semiconductor fabs are taking an ‘all hands on deck’ approach to solving tough metrology and yield management challenges, combining tools, processes, and other technologies as the chip industry transitions to nanosheet transistors on the front end and heterogenous integration on the back end. Optical and e-beam tools are being extended, while X-ray inspection is being added on a case-by-... » read more

Looking Inside Of Chips


Shai Cohen, co-founder and CEO of proteanTecs, sat down with Semiconductor Engineering to talk about how to boost reliability and add resiliency into chips and advanced packaging. What follows are excerpts of that conversation. SE: Several years ago, no one was thinking about on-chip monitoring. What's changed? Cohen: Today it is obvious that a solution is needed for optimizing performanc... » read more

Achieving Greater Accuracy In Real-Time Vision Processing With Transformers


Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications and got interesting results. While previously, vision tasks had been dominated by convolutional neural networks (CNNs), transformers have proven surprisingly adaptable to vision tasks like image cl... » read more

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