Will Stochastic Devices Play Nice With Others in Neuromorphic Hardware?: There’s More to a Probabilistic System Than Noisy Devices

Aimone, James B.; Misra, Shashank

doi:10.1109/med.2023.3298873

Will Stochastic Devices Play Nice With Others in Neuromorphic Hardware?: There’s More to a Probabilistic System Than Noisy Devices

Journal Article · Fri Sep 01 00:00:00 EDT 2023 · IEEE Electron Devices Magazine

DOI:https://doi.org/10.1109/med.2023.3298873· OSTI ID:2311438

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Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Achieving brain-like efficiency in computing requires a co-design between the development of neural algorithms, brain-inspired circuit design, and careful consideration of how to use emerging devices. The recognition that leveraging device-level noise as a source of controlled stochasticity represents an exciting prospect of achieving brain-like capabilities in probabilistic neural algorithms, but the reality of integrating stochastic devices with deterministic devices in an already-challenging neuromorphic circuit design process is formidable. Here, we explore how the brain combines different signaling modalities into its neural circuits as well as consider the implications of more tightly integrated stochastic, analog, and digital circuits. Further, by acknowledging that a fully CMOS implementation is the appropriate baseline, we conclude that if mixing modalities is going to be successful for neuromorphic computing, it will be critical that device choices consider strengths and limitations at the overall circuit level.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: NA0003525

OSTI ID:: 2311438

Report Number(s):: SAND--2023-13765J

Journal Information:: IEEE Electron Devices Magazine, Journal Name: IEEE Electron Devices Magazine Journal Issue: 2 Vol. 1; ISSN 2832-7683

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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