Zobrazeno 1 - 10
of 263
pro vyhledávání: '"Demara, Ronald F."'
The fast development of object detection techniques has attracted attention to developing efficient Deep Neural Networks (DNNs). However, the current state-of-the-art DNN models can not provide a balanced solution among accuracy, speed, and model siz
Externí odkaz:
http://arxiv.org/abs/2408.01534
Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation
Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM) probabilistic device (p-bit) as the basis of neuronal structures in
Externí odkaz:
http://arxiv.org/abs/2005.00923
Magnetic Random-Access Memory (MRAM) based p-bit neuromorphic computing devices are garnering increasing interest as a means to compactly and efficiently realize machine learning operations in Restricted Boltzmann Machines (RBMs). When embedded withi
Externí odkaz:
http://arxiv.org/abs/2002.00897
Autor:
Salehi, Soheil, DeMara, Ronald F.
A Compressive Sensing (CS) approach is applied to utilize intrinsic computation capabilities of Spin-Orbit Torque Magnetic Random Access Memory (SOT-MRAM) devices for IoT applications wherein lifetime energy, device area, and manufacturing costs are
Externí odkaz:
http://arxiv.org/abs/1911.08633
Publikováno v:
In Internet of Things July 2023 22
Autor:
Roohi, Arman, DeMara, Ronald F
Energy-harvesting-powered computing offers intriguing and vast opportunities to dramatically transform the landscape of the Internet of Things (IoT) devices by utilizing ambient sources of energy to achieve battery-free computing. In order to operate
Externí odkaz:
http://arxiv.org/abs/1904.10564
Herein, a bit-wise Convolutional Neural Network (CNN) in-memory accelerator is implemented using Spin-Orbit Torque Magnetic Random Access Memory (SOT-MRAM) computational sub-arrays. It utilizes a novel AND-Accumulation method capable of significantly
Externí odkaz:
http://arxiv.org/abs/1904.07864
In this paper, we develop a 6-input fracturable non-volatile Clockless LUT (C-LUT) using spin Hall effect (SHE)-based Magnetic Tunnel Junctions (MTJs) and provide a detailed comparison between the SHE-MTJ-based C-LUT and Spin Transfer Torque (STT)-MT
Externí odkaz:
http://arxiv.org/abs/1903.00978
Recently, the promising aspects of compressive sensing have inspired new circuit-level approaches for their efficient realization within the literature. However, most of these recent advances involving novel sampling techniques have been proposed wit
Externí odkaz:
http://arxiv.org/abs/1903.00971
Autor:
Zand, Ramtin, DeMara, Ronald F.
In this paper, a spintronic neuromorphic reconfigurable Array (SNRA) is developed to fuse together power-efficient probabilistic and in-field programmable deterministic computing during both training and evaluation phases of restricted Boltzmann mach
Externí odkaz:
http://arxiv.org/abs/1901.02415