Research Bits: Feb. 27


Phonon-magnon reservoir Researchers from TU Dortmund, Loughborough University, V. E. Lashkaryov Institute of Semiconductor Physics, and University of Nottingham were inspired by the human eye to propose an on-chip phonon-magnon reservoir for neuromorphic computing. In reservoir computing, input signals are mapped into a multidimensional space, which is not trained and only expedites recogni... » read more

Novel Neuromorphic Artificial Neural Network Circuit Architecture


A technical paper titled “Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems” was published by researchers at CEA-LETI Université Grenoble Alpes, University of Zurich and ETH Zurich. Abstract: "The brain’s connectivity is locally dense and globally sparse, forming a small-world graph—a principle prevalent in the evolution of various species, sugg... » read more

Ferroelectric Tunnel Junctions In Crossbar Array Analog In-Memory Compute Accelerators


A technical paper titled “Ferroelectric Tunnel Junction Memristors for In-Memory Computing Accelerators” was published by researchers at Lund University. Abstract: "Neuromorphic computing has seen great interest as leaps in artificial intelligence (AI) applications have exposed limitations due to heavy memory access, with the von Neumann computing architecture. The parallel in-memory comp... » read more

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

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