Physical Neural Networks: A Survey (U. of Lübeck, TU Hamburg)


Researchers from the University of Lübeck and TU Hamburg published a technical paper titled “Beyond Silicon: Materials, Mechanisms, and Methods for Physical Neural Computing.” Abstract: “Physical implementations of neural computation now extend far beyond silicon hardware, encompassing substrates such as memristive devices, photonic circuits, mechanical metamaterials, microfluidic netwo... » read more

ReRAM-based Neo-Hebbian Synapses For Training Neuromorphic HW (IIT Madras, UCSB)


A new technical paper, "NeoHebbian synapses to accelerate online training of neuromorphic hardware," was published by researchers at IIT Madras and UC Santa Barbara. Abstract "Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRA... » read more

Neuromorphic HW That Detects Motion Changes 4X Faster (Beihang, BIT, KAUST, Cambridge et al.)


A new technical paper titled "Ultrafast visual perception beyond human capabilities enabled by motion analysis using synaptic transistors" was published by researchers at Beihang University, Beijing Institute of Technology, KAUST, University of Cambridge and others. Excerpt from Abstract "We introduce a neuromorphic temporal-attention hardware that emulates the interaction between the ret... » read more

Hypergraph-based Techniques To Map Spiking Neural Networks on Neuromorphic HW (Politecnico di Milano)


A new technical paper titled "A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware" was published by researchers at Politecnico di Milano. Abstract "Executing Spiking Neural Networks (SNNs) on neuromorphic hardware poses the problem of mapping neurons to cores. SNNs operate by propagating spikes between neurons that form a graph through synapses. Neuromorphic hardware mimic... » read more

Sparse Finite Element Problems on Neuromorphic HW (Sandia National Lab)


A new technical paper titled "Solving sparse finite element problems on neuromorphic hardware" was published by researchers at Sandia National Lab. Abstract "The finite element method (FEM) is one of the most important and ubiquitous numerical methods for solving partial differential equations (PDEs) on computers for scientific and engineering discovery. Applying the FEM to larger and mor... » read more

SpiNNaker2 Neuromorphic Platform: HW-Aware Fine-Tuning of Spiking Q-Networks (TU Dresden Et Al.)


A new technical paper titled "Hardware-Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform" was published by researchers at TU Dresden, ScaDS.AI and Centre for Tactile Internet with Human-in-the-Loop (CeTI). Excerpt "Spiking Neural Networks (SNNs) promise orders-of-magnitude lower power consumption and low-latency inference on neuromorphic hardware for a wide ran... » 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

3D-Integrated Neuromorphic Hardware With A Two-Level Neuromorphic “Synapse Over Neuron” Structure


A technical paper titled “3D Neuromorphic Hardware with Single Thin-Film Transistor Synapses Over Single Thin-Body Transistor Neurons by Monolithic Vertical Integration” was published by researchers at Korea Advanced Institute of Science and Technology (KAIST) and SK hynix. Abstract: "Neuromorphic hardware with a spiking neural network (SNN) can significantly enhance the energy efficiency... » read more

Recent Developments in Neuromorphic Computing, Focusing on Hardware Design and Reliability


A new technical paper titled "Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies" was published by researchers at Univ. Lyon, Ecole Centrale de Lyon, Univ. Grenoble Alpes, Hewlett Packard Labs, CEA-LETI, and Politecnico di Torino. Abstract "The field of neuromorphic computing has been rapidly evolving in recent years, with an incre... » read more

Novel Spintronic Neuro-mimetic Device Emulating the LIF Neuron Dynamics w/High Energy Efficiency & Compact Footprints


New technical paper titled "Noise resilient leaky integrate-and-fire neurons based on multi-domain spintronic devices" from researchers at Purdue University. Abstract "The capability of emulating neural functionalities efficiently in hardware is crucial for building neuromorphic computing systems. While various types of neuro-mimetic devices have been investigated, it remains challenging to... » read more

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