19 papers · ranked by Valyu relevance
Eveline R. W. van Doremaele, Tim Stevens, Stijn Ringeling, Simone Spolaor + 2 more
'Simone Spolaor' 'Marco Fattori' 'Yoeri van de Burgt'] Neural network training can be slow and energy-expensive due to the frequent transfer of weight data between digital memory and processing units. Neuromorphic systems can accelerate neural networks by performing multiply-accumulate operations in parallel using…
Vivek Parmar, Bogdan Penkovsky, Damien Querlioz, Manan Suri
With recent advances in the field of artificial intelligence (AI) such as binarized neural networks (BNNs), a wide variety of vision applications with energy-optimized implementations have become possible at the edge. Such networks have the first layer implemented with high precision, which poses a challenge in…
Hasan Abdel Aziz Mohamed, Mariam Taher, Hossam Moetaz Shousha, Ziad Mohsen + 3 more
The era of the Internet of Things (IoT) introduces new technologies alongside challenges in hardware and data transfer security. This work presents the hardware implementation of the Lightweight Cryptography (LWC) algorithm ASCON-128, specifically targeting IoT applications and edge devices with stringent power and…
Lei Deng, Huajin Tang, Kaushik Roy
Neuromorphic models enjoy low computational costs owing to the binary spike representation and sparse operations. However, directly executing SNNs on GPUs without tailored optimization is inefficient. Neuromorphic hardware is designed for the efficient execution of SNNs via event-driven computing (Merolla et al., ). In…
Pervesh Kumar, Huo Yingge, Imran Ali, Young-Gun Pu + 7 more
'Keum-Cheol Hwang' 'Youngoo Yang' 'Yeon-Jae Jung' 'Hyung-Ki Huh' 'Seok-Kee Kim' 'Joon-Mo Yoo' 'Kang-Yoon Lee'] This paper presents a register-transistor level (RTL) based convolutional neural network (CNN) for biosensor applications. Biosensor-based diseases detection by DNA identification using biosensors is currently…
Zofia Długosz, Michał Rajewski, Rafał Długosz, Tomasz Talaśka + 1 more
'Adam Krzyzak'] In this work, we propose a novel metaheuristic algorithm that evolved from a conventional particle swarm optimization (PSO) algorithm for application in miniaturized devices and systems that require low energy consumption. The modifications allowed us to substantially reduce the computational complexity…
Leila Bagheriye, Johan Kwisthout
The implementation of inference (i.e., computing posterior probabilities) in Bayesian networks using a conventional computing paradigm turns out to be inefficient in terms of energy, time, and space, due to the substantial resources required by floating-point operations. A departure from conventional computing systems…
Yuehai Chen, Huarun Chen, Shaozhen Chen, Chao Han + 6 more
'Yijun Liu' 'Huihui Zhou' 'Mikolaj Karpinski' 'Oleksandr O. Kuznetsov' 'Oleksandr V. Lemeshko'] A Trusted Execution Environment (TEE) is an efficient way to secure information. To obtain higher efficiency, the building of a dual-core system-on-chip (SoC) with TEE security capabilities is the hottest topic. However, TEE…
Goran Savić, Milan Prokin, Vladimir Rajović, Dragana Prokin + 1 more
'Kuo-Liang Chung'] Increasing the resolution of digital images and the frame rate of video sequences leads to an increase in the amount of required logical and memory resources necessary for digital image and video decompression. Therefore, the development of new hardware architectures for digital image decoder with a…
Andrea Manni, Andrea Caroppo, Gabriele Rescio, Pietro Siciliano + 2 more
'Alessandro Leone' 'Francesco Lamonaca'] Heart rate monitoring is especially important for aging individuals because it is associated with longevity and cardiovascular risk. Typically, this vital parameter can be measured using wearable sensors, which are widely available commercially. However, wearable sensors have…
Francesco Porreca, Fabio Frustaci, Raffaele Gravina, Alfio Dario Grasso
Wearable devices can be developed using hardware platforms such as Application Specific Integrated Circuits (ASICs), Graphics Processing Units (GPUs), Digital Signal Processors (DSPs), Micro controller Units (MCUs), or Field Programmable Gate Arrays (FPGAs), each with distinct advantages and limitations. ASICs offer…
Jesús Fernández-Conde, Gwanggil Jeon
In real-time data-intensive applications, achieving real-time data acquisition from sensors and simultaneous storage with the necessary performance is challenging, especially if “no-data-lost” requirements are present. Ad hoc solutions are generally expensive and suffer from a lack of modularity and scalability. In…
Wiktoria Agata Pawlak, Newton Howard
Neuromorphic computing technologies are about to change modern computing, yet most work thus far has emphasized hardware development. This review focuses on the latest progress in algorithmic advances specifically for potential use in brain implants. We discuss current algorithms and emerging neurocomputational models…
Guido Trensch, Abigail Morrison
Despite the great strides neuroscience has made in recent decades, the underlying principles of brain function remain largely unknown. Advancing the field strongly depends on the ability to study large-scale neural networks and perform complex simulations. In this context, simulations in hyper-real-time are of high…
Corneliu Zaharia, Vlad Popescu, Florin Sandu, Zhaoyang Wang + 2 more
'Minh P. Vo' 'Hieu Nguyen'] Computer vision algorithms implementations, especially for real-time applications, are present in a variety of devices that we are currently using (from smartphones or automotive applications to monitoring/security applications) and pose specific challenges, memory bandwidth or energy…
Jingqi Zhang, Zhiming Chen, Xiang He, Kuanhao Liu + 6 more
'Mingzhi Ma' 'Weijiang Wang' 'Hua Dang' 'Xiangnan Li' 'Zhongrui Wang'] Physically unclonable functions (PUFs) are crucial for enhancing cybersecurity by providing unique, intrinsic identifiers for electronic devices, thus ensuring their authenticity and preventing unauthorized cloning. The SRAM-PUF, characterized by…
Ionel Zagan, Vasile Gheorghiţă Găitan, Muhammad Aleem
One of the fundamental requirements of a real-time system (RTS) is the need to guarantee re-al-time determinism for critical tasks. Task execution rates, operating system (OS) overhead, and task context switching times are just a few of the parameters that can cause jitter and missed deadlines in RTS with soft…
Wei Ou, Shitao Xiao, Chengyu Zhu, Wenbao Han + 1 more
With the development of technology, Moore's law will come to an end, and scientists are trying to find a new way out in brain-like computing. But we still know very little about how the brain works. At the present stage of research, brain-like models are all structured to mimic the brain in order to achieve some of the…
Dmitry Ivanov, Aleksandr Chezhegov, Mikhail Kiselev, Andrey Grunin + 1 more
'Denis Larionov'] Modern artificial intelligence (AI) systems, based on von Neumann architecture and classical neural networks, have a number of fundamental limitations in comparison with the mammalian brain. In this article we discuss these limitations and ways to mitigate them. Next, we present an overview of…