CAPSL Probabilistic Spin Logic for Low-Energy Boolean and Non-Boolean Computing

CAPSL Publications 2019

Journal Articles:

2019

  1. V. Ostwal and J. Appenzeller
    Spin-orbit torque controlled Magnetic Tunnel Junction with low thermal stability for tunable random number generation
    IEEE Magnetics Letters 10, 4503305-1 – 4503305-5 (2019).
  2. O. Hassan, R. Faria, K.Y. Camsari, J.Z. Sun, and S. Datta
    Energy and Delay of Hardware Binary Stochastic Neurons
    IEEE Magnetics Letters 10, 4502805-1 – 4502805-5 (2019).
  3. R. Zand, K. Y. Camsari, S. Datta, and R. F. DeMara
    Composable Probabilistic Inference Networks using MRAM-based Stochastic Neurons
    ACM Journal on Emerging Technologies in Computing Systems (JETC), in-press (2019).
    (Selected to Special Issue on Hardware and Algorithms for Energy-Constrained On-chip Machine Learning)

2018

  1. J. Song, I. Ahmed, Z. Zhao, D. Zhang, S. Sapatnekar, J. Wang, and C.H. Kim
    Evaluation of Operating Margin and Switching Probability of Voltage Controlled Magnetic Anisotropy (VCMA) Magnetic Tunnel Junctions
    IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (JxCDC) 4, 76-84 (2018).
  2. R. Zand, K. Y. Camsari, S. Datta, and R. F. DeMara
    Composable Probabilistic Inference Networks using MRAM-based Stochastic Neurons
    arXiv preprint arXiv:1811.11390 (2018).
  3. S. D. Pyle, K. Camsari, and R. F. DeMara
    Hybrid Spin-CMOS Stochastic Spiking Neuron for High-Speed Emulation of In-Vivo Neuron Dynamics
    IET Computers & Digital Techniques 12, 122-129 (2018).
  4. D. Punyashloka and Z. Chen
    Experimental Demonstration of a Spin Logic Device with Deterministic and Stochastic Mode of Operation
    Scientific reports 8, 11405 (2018).
  5. D. Punyashloka, R. Faria, K.Y. Camsari, and Z. Chen
    Design of Stochastic Nanomagnets for Probabilistic Spin Logic
    IEEE Magnetics Letters 9, 1-5 (2018).
  6. V. Ostwal, D. Punyashloka, F. Rafatul, Z. Chen, and J. Appenzeller
    Spin-torque devices with hard axis initialization as Stochastic Binary Neurons
    Scientific reports 8, 16689 (2018).

Conference Proceedings:

2019

  1. D. Punyashloka, P. Upadhyaya and Z. Chen
    Electrical Annealing and Stochastic Resonance in Low Barrier Perpendicular Nanomagnets for Oscillatory NeuralNetworks
    77th Device Research Conference (DRC), (2019).
  2. M. Eisinger, R. Zand, A. Adepegba, and R. F. DeMara
    Training Optimization of Restricted Boltzmann Machines using a Contrastive Divergence Algorithm
    Proceedings of 2019 IEEE Southeastern Conference (SECon-2019), Huntsville, AL, USA, April 11-14 (2019).
  3. A. Adepegba, R. Zand, and R. F. DeMara
    Noise Sensitivity Analysis of Deep Belief Networks: A Monte Carlo Simulation for Memristive Crossbars
    Proceedings of 2019 IEEE Southeastern Conference (SECon-2019), Huntsville, AL, USA, April 11-14 (2019).

2018

  1. R. Zand and R. F. DeMara
    SNRA: A Spintronic Neuromorphic Reconfigurable Array for In-Circuit Training and Evaluation of Deep Belief Networks
    Proceedings of IEEE International Conference on Rebooting Computing (ICRC-2018), pp. 1-8, Washington, DC, USA, November 7-9 (2018).
  2. R. Zand, K. Y. Camsari, S. D. Pyle, I. Ahmed, C. H. Kim, and R. F. DeMara
    Low-Energy Deep Belief Networks using Intrinsic Sigmoidal Spintronic-based Probabilistic Neurons
    Proceedings of 27th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI-2018), Chicago, IL, USA, May 23-25 (2018).
  3. D. Punyashloka and Z. Chen
    Tunable Random Number Generation Using Single Superparamagnet with Perpendicular Magnetic Anisotropy
    76th Device Research Conference (DRC), pp. 1-2. (2018).

2017

  1. R. F. DeMara, A. Roohi, R. Zand, and S. D. Pyle
    Heterogeneous Technology Configurable Fabrics for Field Programmable Co-design of CMOS and Spin-based Devices
    Proceedings of IEEE International Conference on Rebooting Computing (ICRC-2017), pp. 1-4, Washington, DC, USA, November 8-9 (2017).