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LowPy: Simulation Platform for Machine Learning Algorithm Realization in Neuromorphic RRAM-Based Processors

Ford, Andrew J
http://orcid.org/0000-0001-9251-3724
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617105323741119

Abstract Details

2021, MS, University of Cincinnati, Engineering and Applied Science: Electrical Engineering.
A novel compilation of non-ideal characteristics which accompany hardware realizations of machine learning algorithms in the form RRAM-based neuromorphic ASIC processors is presented within a convenient, simple, and powerful simulation library named LowPy for use with Python. Simulations results are shown for four different networks; SLP, MLP, CNN, and LSTM. Each is subjected to six different GPU-accelerated nonideality functions backed by experimentally gathered data, as well as data provided by external research. Of the six nonideality functions, a spread of selected parameters is chosen such that any performance impacts of the algorithm are easily observed across several orders of magnitude. Main aspects differentiating LowPy from other neuromorphic simulation platforms include functions not yet implemented by other platforms, the most non-ideal functions provided by any platform known by the author to date, an event-driven architecture that provides the user full control over which and when nonideality functions are executed during training and testing, as well as its ability to wrap around an existing well-documented, popular, GPU-accelerated machine learning library.
Rashmi Jha, Ph.D. (Committee Chair)
John Emmert, Ph.D. (Committee Member)
Ranganadha Vemuri, Ph.D. (Committee Member)
93 p.
Electrical Engineering
RRAM; neuromorphic computing; non-ideal behavior; simulator

Recommended Citations

Citations

  • Ford, A. J. (2021). LowPy: Simulation Platform for Machine Learning Algorithm Realization in Neuromorphic RRAM-Based Processors [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617105323741119

    APA Style (7th edition)

  • Ford, Andrew. LowPy: Simulation Platform for Machine Learning Algorithm Realization in Neuromorphic RRAM-Based Processors. 2021. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617105323741119.

    MLA Style (8th edition)

  • Ford, Andrew. "LowPy: Simulation Platform for Machine Learning Algorithm Realization in Neuromorphic RRAM-Based Processors." Master's thesis, University of Cincinnati, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1617105323741119

    Chicago Manual of Style (17th edition)

ucin1617105323741119
105
© 2021, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.