Single Transistor Memory Cell C2RAM Based On FDSOI For Quantum And Neuromorphic


A new technical paper titled "An Energy Efficient Memory Cell for Quantum and Neuromorphic Computing at Low Temperatures" was published by researchers at Forschungszentrum Jülich, RWTH Aachen University and SOITEC. Abstract: "Efficient computing in cryogenic environments, including classical von Neumann, quantum, and neuromorphic systems, is poised to transform big data processing. The que... » read more

ReRAM-Based, In-Memory Implementation Of Stochastic Computing


A new technical paper titled "All-in-Memory Stochastic Computing using ReRAM" was published by researchers at TU Dresden, Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Case Western Reserve University, University of Louisiana at Lafayette and Barkhausen Institut. Abstract "As the demand for efficient, low-power computing in embedded and edge devices grows, tradit... » read more

GenAI for Analog IC Design (McMaster University)


A new technical paper titled "Generative AI for Analog Integrated Circuit Design: Methodologies and Applications" was published by researchers at McMaster University. Abstract "Electronic Design Automation (EDA) in analog Integrated Circuits (ICs) has been the focus of extensive research; however, unlike its digital counterpart, it has not achieved widespread adoption. In this systematic re... » read more

Side-by-Side Benchmark of NPU Platforms (Imperial College London, Cambridge)


A new technical paper titled "Benchmarking Ultra-Low-Power μNPUs" was published by researchers at Imperial College London and University of Cambridge. Abstract "Efficient on-device neural network (NN) inference has various advantages over cloud-based processing, including predictable latency, enhanced privacy, greater reliability, and reduced operating costs for vendors. This has sparked t... » read more

LLM-based Agentic Framework Automating HW Security Threat Modeling And Test Plan Generation (U. of Florida)


A new technical paper titled "ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification" was published by researchers at University of Florida. Abstract "Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing ... » read more

Scalable And Energy Efficient Solution for Hardware-Based ANNs (KAUST, NUS)


A new technical paper titled "Synaptic and neural behaviours in a standard silicon transistor" was published by researchers at KAUST and National University of Singapore. Abstract "Hardware implementations of artificial neural networks (ANNs)—the most advanced of which are made of millions of electronic neurons interconnected by hundreds of millions of electronic synapses—have achieved ... » read more

GPU Analysis Identifying Performance Bottlenecks That Cause Throughput Plateaus In Large-Batch Inference


A new technical paper titled "Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference" was published by researchers at Barcelona Supercomputing Center, Universitat Politecnica de Catalunya, and IBM Research. Abstract "Large language models have been widely adopted across different tasks, but their auto-regressive generation nature often leads to inefficient resource util... » read more

HW Implementation Of An ONN Coupled By A ReRAM Crossbar Array (IBM, TU Eindhoven)


A new technical paper titled "Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks" was published by researchers at IBM Research Europe and Eindhoven University of Technology. Abstract "We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. ... » read more

Energy-Efficient Scalable Silicon Photonic Platform For AI Accelerator HW


A new technical paper titled "Large-Scale Integrated Photonic Device Platform for Energy-Efficient AI/ML Accelerators" was published by researchers at HP Labs, IIT Madras, Microsoft Research and University of Michigan. Abstract "The convergence of deep learning and Big Data has spurred significant interest in developing novel hardware that can run large artificial intelligence (AI) workload... » read more

The Optical Implementation of Backpropagation (Oxford, Lumai)


A technical paper titled "Training neural networks with end-to-end optical backpropagation" was published by researchers at University of Oxford and Lumai Ltd. Abstract "Optics is an exciting route for the next generation of computing hardware for machine learning, promising several orders of magnitude enhancement in both computational speed and energy efficiency. However, reaching the full... » read more

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