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ORCIDICRC 2020: Atlanta, GA, USA
- International Conference on Rebooting Computing, ICRC 2020, Atlanta, GA, USA, December 1-3, 2020. IEEE 2020, ISBN 978-1-6654-1975-8
- Michael P. Frank, Robert W. Brocato, Brian D. Tierney, Nancy A. Missert, Alexander H. Hsia:
Reversible Computing with Fast, Fully Static, Fully Adiabatic CMOS. 1-8 - Rene Celis-Cordova, Alexei O. Orlov, Gregory L. Snider
, Tian Lu, Jason M. Kulick:
Adiabatic Flip-Flop and SRAM Design for an Adiabatic Reversible Microprocessor. 9-15 - Valeriu Beiu, Vlad-Florin Dragoi, Roxana-Mariana Beiu:
Why Reliability for Computing Needs Rethinking. 16-25 - Kyle Henke, Ben Migliori, Garrett T. Kenyon:
Alien vs. Predator: Brain Inspired Sparse Coding Optimization on Neuromorphic and Quantum Devices. 26-33 - Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Advanced unembedding techniques for quantum annealers. 34-41 - Erik P. DeBenedictis:
Adiabatic Circuits for Quantum Computer Control. 42-49 - Christoph Roch, Alexander Impertro, Thomy Phan, Thomas Gabor, Sebastian Feld, Claudia Linnhoff-Popien:
Cross Entropy Hyperparameter Optimization for Constrained Problem Hamiltonians Applied to QAOA. 50-57 - Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov:
Tucker-1 Boolean Tensor Factorization with Quantum Annealers. 58-65 - Anastasiia Butko, George Michelogiannakis, Samuel Williams, Costin Iancu, David Donofrio, John Shalf, Jonathan Carter, Irfan Siddiqi:
Understanding Quantum Control Processor Capabilities and Limitations through Circuit Characterization. 66-75 - Suhas Kumar, Thomas Van Vaerenbergh, John Paul Strachan:
Classical Adiabatic Annealing in Memristor Hopfield Neural Networks for Combinatorial Optimization. 76-79 - Natesh Ganesh:
Rebooting Neuromorphic Design - A Complexity Engineering Approach. 80-89 - Bruno U. Pedroni, Stephen R. Deiss, Nishant Mysore, Gert Cauwenberghs:
Design Principles of Large-Scale Neuromorphic Systems Centered on High Bandwidth Memory. 90-94 - Jun Shiomi, Tohru Ishihara, Hidetoshi Onodera, Akihiko Shinya, Masaya Notomi:
An Optical Accelerator for Deep Neural Network Based on Integrated Nanophotonics. 95-101 - Ruomin Zhu, Joel Hochstetter, Alon Loeffler, Adrian Diaz-Alvarez, Adam Z. Stieg, James K. Gimzewski, Tomonobu Nakayama, Zdenka Kuncic:
Harnessing adaptive dynamics in neuro-memristive nanowire networks for transfer learning. 102-106 - Prasanna Date, Christopher D. Carothers, John E. Mitchell, James A. Hendler, Malik Magdon-Ismail:
Training Deep Neural Networks with Constrained Learning Parameters. 107-115 - James S. Plank, Jiajia Zhao, Brent Hurst:
Reducing the Size of Spiking Convolutional Neural Networks by Trading Time for Space. 116-125 - Sourabh Kulkarni, Alexander Tsyplikhin, Mario Michael Krell, Csaba Andras Moritz:
Accelerating Simulation-based Inference with Emerging AI Hardware. 126-132 - Jeff Anderson, Engin Kayraklioglu, Hamid Reza Imani, Mario Miscuglio, Volker J. Sorger, Tarek A. El-Ghazawi:
Virtualizing Analog Mesh Computers: The Case of a Photonic PDE Solving Accelerator. 133-142
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