45 citations · 102 across the 11 of their papers we have counts for
9 papers · 1 filter
Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation
Hossein Pourmeidani, Punyashloka Debashis, Zhihong Chen +2
Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM…
Modular Simulation Framework for Process Variation Analysis of MRAM-based Deep Belief Networks
Paul Wood, Hossein Pourmeidani, Ronald F. DeMara
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 o…
Adaptive Non-Uniform Compressive Sensing using SOT-MRAM Multibit Crossbar Arrays
Soheil Salehi, Ronald F. DeMara
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 applicati…
IRC: Cross-layer design exploration of Intermittent Robust Computation units for IoTs
Arman Roohi, Ronald F DeMara
Energy-harvesting-powered computing offers intriguing and vast opportunities to dramatically transform the landscape of the Internet of Things (IoT) devices by utilizing ambient so…
Clockless Spin-based Look-Up Tables with Wide Read Margin
Soheil Salehi, Ramtin Zand, Ronald F. DeMara
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 compar…
AQuRate: MRAM-based Stochastic Oscillator for Adaptive Quantization Rate Sampling of Sparse Signals
Soheil Salehi, Ramtin Zand, Alireza Zaeemzadeh +2
Recently, the promising aspects of compressive sensing have inspired new circuit-level approaches for their efficient realization within the literature. However, most of these rece…
SNRA: A Spintronic Neuromorphic Reconfigurable Array for In-Circuit Training and Evaluation of Deep Belief Networks
Ramtin Zand, Ronald F. DeMara
In this paper, a spintronic neuromorphic reconfigurable Array (SNRA) is developed to fuse together power-efficient probabilistic and in-field programmable deterministic computing d…
Composable Probabilistic Inference Networks Using MRAM-based Stochastic Neurons
Ramtin Zand, Kerem Y. Camsari, Supriyo Datta +1
Magnetoresistive random access memory (MRAM) technologies with thermally unstable nanomagnets are leveraged to develop an intrinsic stochastic neuron as a building block for restri…
Low-Energy Deep Belief Networks using Intrinsic Sigmoidal Spintronic-based Probabilistic Neurons
Ramtin Zand, Kerem Yunus Camsari, Steven D. Pyle +3
A low-energy hardware implementation of deep belief network (DBN) architecture is developed using near-zero energy barrier probabilistic spin logic devices (p-bits), which are mode…