category: AI/ML/DL

category: IoT, Security & Automotive

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs
By Technical Paper Link - 14 Mar, 2022 - Comments: 0

Abstract: "When deep neural network (DNN) is extensively utilized for edge AI (Artificial Intelligence), for example, the Internet of things (IoT) and autonomous vehicles, it makes CMOS (Complementary Metal Oxide Semiconductor)-based conventional computers suffer from overly large computing loads. Memristor-based devices are emerging as an option to conduct computing in memory for DNNs to make... » read more

Multi-Task Network Pruning and Embedded Optimization for Real-time Deployment in ADAS
By Technical Paper Link - 15 Feb, 2022 - Comments: 0

Abstract: "Camera-based Deep Learning algorithms are increasingly needed for perception in Automated Driving systems. However, constraints from the automotive industry challenge the deployment of CNNs by imposing embedded systems with limited computational resources. In this paper, we propose an approach to embed a multi- task CNN network under such conditions on a commercial prototy... » read more

Reservoir Computing based on Mutually Injected Phase Modulated Semiconductor Lasers as a Monolithic Integrated Hardware Accelerator
By Technical Paper Link - 08 Feb, 2022 - Comments: 0

Abstract: "In this paper we propose and numerically study a neuromorphic computing scheme that applies delay-based reservoir computing in a laser system consisting of two mutually coupled phase modulated lasers. The scheme can be monolithic integrated in a straightforward manner and alleviates the need for external optical injection, as the data can be directly applied on the on-chip phase m... » read more

Non-destructive Thickness Characterisation of 3D Multilayer Semiconductor Devices Using Optical Spectral Measurements and Machine Learning
By Technical Paper Link - 07 Feb, 2022 - Comments: 0

Abstract: "Three-dimensional (3D) semiconductor devices can address the limitations of traditional two-dimensional (2D) devices by expanding the integration space in the vertical direction. A 3D NOT-AND (NAND) flash memory device ispresently the most commercially successful 3D semiconductor device. It vertically stacks more than 100 semiconductor material layers to provide more storage capac... » read more

Inverse Design of Inflatable Soft Membranes Through Machine Learning
By Technical Paper Link - 27 Jan, 2022 - Comments: 0

Abstract "Across fields of science, researchers have increasingly focused on designing soft devices that can shape-morph to achieve functionality. However, identifying a rest shape that leads to a target 3D shape upon actuation is a non-trivial task that involves inverse design capabilities. In this study, a simple and efficient platform is presented to design pre-programmed 3D shapes starting... » read more

Next Generation Reservoir Computing
By Technical Paper Link - 18 Jan, 2022 - Comments: 0

Abstract: "Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural n... » read more

A crossbar array of magnetoresistive memory devices for in-memory computing
By Technical Paper Link - 14 Jan, 2022 - Comments: 0

Samsung has demonstrated the world’s first in-memory computing technology based on MRAM. Samsung has a paper on the subject in Nature. This paper showcases Samsung’s effort to merge memory and system semiconductors for next-generation artificial intelligence (AI) chips. Abstract "Implementations of artificial neural networks that borrow analogue techniques could potentially offer low-po... » read more

Always-On Sub-Microwatt Spiking Neural Network Based on Spike-Driven Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device
By Technical Paper Link - 21 Dec, 2021 - Comments: 0

Abstract: "This paper presents a novel spiking neural network (SNN) classifier architecture for enabling always-on artificial intelligent (AI) functions, such as keyword spotting (KWS) and visual wake-up, in ultra-low-power internet-of-things (IoT) devices. Such always-on hardware tends to dominate the power efficiency of an IoT device and therefore it is paramount to minimize its power diss... » read more

An Event-Driven and Fully Synthesizable Architecture for Spiking Neural Networks
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:  "The development of brain-inspired neuromorphic computing architectures as a paradigm for Artificial Intelligence (AI) at the edge is a candidate solution that can meet strict energy and cost reduction constraints in the Internet of Things (IoT) application areas. Toward this goal, we present μBrain: the first digital yet fully event-driven without clock architecture, with co-lo... » read more

NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:   "Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with options of various mainstream and emerging memory technologies, architectures, and networks can be a great convenience for fast early-stage design space exploration of CIM hardw... » read more

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2025 SMG   |  Terms of Service  |  Privacy Policy