SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing

Author:

Date Prasanna1ORCID,Gunaratne Chathika1ORCID,R. Kulkarni Shruti1ORCID,Patton Robert1ORCID,Coletti Mark1ORCID,Potok Thomas1ORCID

Affiliation:

1. Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

Funder

U.S. Department of Energy

Publisher

ACM

Reference18 articles.

1. Aimone , J. , Date , P. , Fonseca-Guerra , G. , Hamilton , K. , Henke , K. , Kay , B. , Kenyon , G. , Kulkarni , S. , Mniszewski , S. , Parsa , M. , A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering ( 2022 ). Aimone, J., Date, P., Fonseca-Guerra, G., Hamilton, K., Henke, K., Kay, B., Kenyon, G., Kulkarni, S., Mniszewski, S., Parsa, M., et al. A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering (2022).

2. Acceleration of spiking neural networks in emerging multi-core and GPU architectures

3. Semi-Supervised Graph Structure Learning on Neuromorphic Computers

4. Efficient Classification of Supercomputer Failures Using Neuromorphic Computing

5. Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

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1. CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool;2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2024-05-05

2. Arithmetic Primitives for Efficient Neuromorphic Computing;2023 IEEE International Conference on Rebooting Computing (ICRC);2023-12-05

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