3 citations · 8 across the 7 of their papers we have counts for
7 papers
CMOS-integrated superparamagnetic tunnel junction-based p-bit
Ju-Young Yoon, Nuno Cacoilo, Advait Madhavan +5
Probabilistic computers offer promising solutions for computationally hard problems in domains such as combinatorial optimization and machine learning. A key building block in thes…
Sampling from exponential distributions in the time domain with superparamagnetic tunnel junctions
Temitayo N. Adeyeye, Sidra Gibeault, Daniel P. Lathrop +8
In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exp…
Scanning Thermal Microscopy in Air and Vacuum: A Comparison
Jabez J. McClelland, Evgheni Strelcov, Ami Chand
We present measurements comparing scanning thermal microscopy in air and vacuum. Signal levels are compared and resolution is probed by scanning over the edge of a nanofabricated A…
Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance
Osama Yousuf, Brian Hoskins, Karthick Ramu +8
Artificial neural networks have advanced due to scaling dimensions, but conventional computing faces inefficiency due to the von Neumann bottleneck. In-memory computation architect…
Measurement-driven Langevin modeling of superparamagnetic tunnel junctions
Liam A. Pocher, Temitayo N. Adeyeye, Sidra Gibeault +7
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing q…
Programmable electrical coupling between stochastic magnetic tunnel junctions
Sidra Gibeault, Temitayo N. Adeyeye, Liam A. Pocher +9
Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of probabilistic computing techniques. Augmenting an…
Measurement-driven neural-network training for integrated magnetic tunnel junction arrays
William A. Borders, Advait Madhavan, Matthew W. Daniels +7
The increasing scale of neural networks needed to support more complex applications has led to an increasing requirement for area- and energy-efficient hardware. One route to meeti…