IMC: Free-Space Optical Neural Network With High Clockrate (Berkeley, USC, TU Berlin)


A new technical paper titled "High-clockrate free-space optical in-memory computing" was published by researchers at UC Berkeley, USC,  and TU Berlin. Abstract "The ability to process and act on data in real time is increasingly critical for applications ranging from autonomous vehicles, three-dimensional environmental sensing, and remote robotics. However, the deployment of deep neural ... » read more

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling


The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and heterogeneous integration strategies. Traditional physics-based modeling approaches are increasingly challenged by nonlinear effects, electro-thermal interactions, and variability across device geometr... » 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

On-Device Speaker Identification For Digital Television (DTV)


In recent years, the way we interact with our TVs has changed. Multiple button presses to navigate an on-screen keyboard have been replaced with direct interaction through our voices. While this has resulted in significant improvements to the Digital Television (DTV) user experience, more can be done to provide immersive and engaging experiences. Imagine you say, “recommend me a film” or... » read more

BYO NPU Benchmarks


In our last blog post, we highlighted the ways that NPU vendors can shade the truth about performance on benchmark networks such that comparing common performance scores such as “Resnet50 Inferences / Second” can be a futile exercise. But there is a straight-forward, low-investment method for an IP evaluator to short-circuit all the vendor shenanigans and get a solid apples-to-apples result... » read more

28nm-HKMG-Based FeFET Devices For Synaptic Applications


A technical paper titled "28 nm high-k-metal gate ferroelectric field effect transistors based synapses- A comprehensive overview" was published by researchers at Fraunhofer-Institut für Photonische Mikrosysteme IPMS, Indian Institute of Technology Madras, and GlobalFoundries. Abstract This invited article we present a comprehensive overview of 28 nm high-k-metal gate-based ferroelectric f... » read more

Autonomous Driving: End-to-End Surround 3D Camera Perception System (NVIDIA)


A new technical paper titled "NVAutoNet: Fast and Accurate 360∘ 3D Visual Perception For Self Driving" was published by researchers at NVIDIA. Abstract "Robust real-time perception of 3D world is essential to the autonomous vehicle. We introduce an end-to-end surround camera perception system for self-driving. Our perception system is a novel multi-task, multi-camera network which takes a... » read more

HW-SW Co-Design Solution For Building Side-Channel-Protected ML Hardware


A technical paper titled "Hardware-Software Co-design for Side-Channel Protected Neural Network Inference" was published (preprint) by researchers at North Carolina State University and Intel. Abstract "Physical side-channel attacks are a major threat to stealing confidential data from devices. There has been a recent surge in such attacks on edge machine learning (ML) hardware to extract the... » read more

Will Floating Point 8 Solve AI/ML Overhead?


While the media buzzes about the Turing Test-busting results of ChatGPT, engineers are focused on the hardware challenges of running large language models and other deep learning networks. High on the ML punch list is how to run models more efficiently using less power, especially in critical applications like self-driving vehicles where latency becomes a matter of life or death. AI already ... » read more

L-FinFET Neuron For A Highly Scalable Capacitive Neural Network (KAIST)


A new technical paper titled "An Artificial Neuron with a Leaky Fin-Shaped Field-Effect Transistor for a Highly Scalable Capacitive Neural Network" was published by researchers at KAIST (Korea Advanced Institute of Science and Technology). “In commercialized flash memory, tunnelling oxide prevents the trapped charges from escaping for better memory ability. In our proposed FinFET neuron, t... » read more

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