activity
20172025
most citedLow Barrier Magnet Design for Efficient Hardware Binary Stochastic Neurons

68 citations · 141 across the 6 of their papers we have counts for

collaborators

6 papers

cs.ET2025

CNN-Based Automated Parameter Extraction Framework for Modeling Memristive Devices

Akif Hamid, Orchi Hassan

Resistive random access memory (RRAM) is a promising candidate for next-generation nonvolatile memory (NVM) and in-memory computing applications. Compact models are essential for a…

physics.app-ph2022★ 5 cited

A Magnetoelectric Memory Device Based on Pseudo-Magnetization

Tingting Shen, Orchi Hassan, Neil R. Dilley +2

We propose a new type of magnetoelectric memory device that stores magnetic easy-axis information or pseudo-magnetization, rather than a definite magnetization direction, in piezoe…

cs.ET2021★ 38 cited

Quantitative Evaluation of Hardware Binary Stochastic Neurons

Orchi Hassan, Supriyo Datta, Kerem Y. Camsari

Recently there has been increasing activity to build dedicated Ising Machines to accelerate the solution of combinatorial optimization problems by expressing these problems as a gr…

cs.ET2019★ 68 cited

Low Barrier Magnet Design for Efficient Hardware Binary Stochastic Neurons

Orchi Hassan, Rafatul Faria, Kerem Y. Camsari +2

Binary stochastic neurons (BSN's) form an integral part of many machine learning algorithms, motivating the development of hardware accelerators for this complex function. It has b…

cs.ET2018★ 21 cited

Voltage-driven Building Block for Hardware Belief Networks

Orchi Hassan, Kerem Y. Camsari, Supriyo Datta

Probabilistic spin logic (PSL), based on networks of binary stochastic neurons (or p-bits), has been shown to provide a viable framework for many functionalities including Ising co…

cond-mat.mes-hall2017★ 9 cited

Equivalent Circuit for Magnetoelectric Read and Write Operations

Kerem Y. Camsari, Rafatul Faria, Orchi Hassan +2

We describe an equivalent circuit model applicable to a wide variety of magnetoelectric phenomena and use SPICE simulations to benchmark this model against experimental data. We us…