Evaluating online-learning in memristive neuromorphic circuits

Conference · Sun Apr 01 00:00:00 EDT 2018

DOI:https://doi.org/10.1145/3183584.3183616· OSTI ID:1435234

Wyer, Austin ^[1]; Adnan, Md Musabbir ^[2]; Woong Ku, Bon ^[3]; Kyu Lim, Sung ^[3]; Schuman, Catherine  ^[4]; Pooser, Raphael  ^[4]; Rose, Garrett ^[2]

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1. University of Tennessee, Knoxville (UTK)
2. University of Tennessee (UT)
3. Georgia Institute of Technology
4. ORNL

In this work we present an implementation of spike-timing-dependent plasticity (STDP) in both a high level simulation and at a circuit level. It is verified that the high level simulation captures the behavior of the circuit implementation. We use the simulation to assess the effectiveness of STDP for online-learning, and find that STDP enables networks to improve performance online after training.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1435234
• Resource Relation: Conference: Neuromorphic Computing Symposium (NCS 2017) - Knoxville, Tennessee, United States of America - 7/17/2017 12:00:00 PM-7/19/2017 8:00:00 AM
• Country of Publication: United States
• Language: English