Research Bits: Jan. 2


Synaptic transistor Researchers from Northwestern University, Boston College, and MIT developed a synaptic transistor that simultaneously processes and stores information similar to the human brain. The team said the transistor goes beyond simple machine learning tasks to categorize data and is capable of performing associative learning. The new device is stable at room temperatures. It als... » read more

A Survey Of Recent Advances In Spiking Neural Networks From Algorithms To HW Acceleration


A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of California Santa Cruz, University of Wisconsin-Madison, and University of Southern California. Abstract: "Neuromorphic computing and, in particular, spiking neural networks (SNNs) have becom... » read more

Neuromorphic Devices Based On Memristive Nanowire Networks


A technical paper titled “Online dynamical learning and sequence memory with neuromorphic nanowire networks” was published by researchers at University of Sydney, University of California Los Angeles (UCLA), National Institute for Materials Science (NIMS), Kyushu Institute of Technology (Kyutech), and University of Sydney Nano Institute. Abstract: "Nanowire Networks (NWNs) belong to an em... » read more

Maximizing Edge Intelligence Requires More Than Computing


By Toshi Nishida, Avik W. Ghosh, Swaminathan Rajaraman, and Mircea Stan Commercial-off-the-shelf (COTS) components have enabled a commodity market for Wi-Fi-connected appliances, consumer products, infrastructure, manufacturing, vehicles, and wearables. However, the vast majority of connected systems today are deployed at the edge of the network, near the end user or end application, opening... » read more

Neuromorphic Hardware Accelerator For Heterogeneous Many-Accelerator SoCs


A technical paper titled “SpikeHard: Efficiency-Driven Neuromorphic Hardware for Heterogeneous Systems-on-Chip” was published by researchers at Columbia University. Abstract: "Neuromorphic computing is an emerging field with the potential to offer performance and energy-efficiency gains over traditional machine learning approaches. Most neuromorphic hardware, however, has been designed wi... » read more

Neuromorphic Artificial Synaptic Device Combining Memristor Arrays With Copper Iodide


A technical paper titled “Charge-Mediated Copper-Iodide-Based Artificial Synaptic Device with Ultrahigh Neuromorphic Efficacy” was published by researchers at University of Glasgow, City University of Hong Kong, and Hong Kong Metropolitan University. Abstract: "In the realm of artificial intelligence, ultrahigh-performance neuromorphic computing plays a significant role in executing multi... » read more

Neuromorphic Computing: Graphene-Based Memristors For Future AI Hardware From Fabrication To SNNs


A technical paper titled “A Review of Graphene-Based Memristive Neuromorphic Devices and Circuits” was published by researchers at James Cook University (Australia) and York University (Canada). Abstract: "As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic computing mimics the brain's... » read more

TaN Nanowires At 300 mm Wafer Scale For Quantum Computing And More


A technical paper titled "Ultra-thin TaN Damascene Nanowire Structures on 300 mm Si Wafers for Quantum Applications" was published by researchers at NY CREATES, United States Air Force Research Laboratory and SUNY Polytechnic Institute. Abstract: "We report on the development and characterization of superconducting damascene tantalum nitride (TaN) nanowires, 100 nm to 3 μm wide, with TaN thi... » read more

Redox-Based Ionic Devices For High-Performance Neuromorphic Computing


A technical paper titled "A Redox-Based Ion-Gating Reservoir, Utilizing Double Reservoir States in Drain and Gate Nonlinear Responses" was published by researchers at National Institute for Materials Science (NIMS) and Tokyo University of Science. Abstract: "Herein, physical reservoir computing with a redox-based ion-gating reservoir (redox-IGR) comprising LixWO3 thin film and lithium-ion co... » read more

DW-MTJ Devices For Noise-Resilient Networks For Neuromorphic Computing On The Edge


A technical paper titled "Stochastic domain wall-magnetic tunnel junction artificial neurons for noise-resilient spiking neural networks" was published by researchers at University of Texas at Austin. Abstract: "The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) makes SNNs promising for edge applications that require high energy efficiency. To realize SNNs in har... » read more

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