Benchmarking Neuromorphic Hardware and Its Energy Expenditure

Ostrau C, Klarhorst C, Thies M, Rückert U (2022)
Frontiers in Neuroscience 16: 873935.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
We propose and discuss a platform overarching benchmark suite for neuromorphic hardware. This suite covers benchmarks from low-level characterization to high-level application evaluation using benchmark specific metrics. With this rather broad approach we are able to compare various hardware systems including mixed-signal and fully digital neuromorphic architectures. Selected benchmarks are discussed and results for several target platforms are presented revealing characteristic differences between the various systems. Furthermore, a proposed energy model allows to combine benchmark performance metrics with energy efficiency. This model enables the prediction of the energy expenditure of a network on a target system without actually having access to it. To quantify the efficiency gap between neuromorphics and the biological paragon of the human brain, the energy model is used to estimate the energy required for a full brain simulation. This reveals that current neuromorphic systems are at least four orders of magnitude less efficient. It is argued, that even with a modern fabrication process, two to three orders of magnitude are remaining. Finally, for selected benchmarks the performance and efficiency of the neuromorphic solution is compared to standard approaches.
Erscheinungsjahr
2022
Zeitschriftentitel
Frontiers in Neuroscience
Band
16
Art.-Nr.
873935
eISSN
1662-453X
Page URI
https://pub.uni-bielefeld.de/record/2963591

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Ostrau C, Klarhorst C, Thies M, Rückert U. Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience. 2022;16: 873935.
Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2022). Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience, 16, 873935. https://doi.org/10.3389/fnins.2022.873935
Ostrau, C., Klarhorst, C., Thies, M., and Rückert, U. (2022). Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience 16:873935.
Ostrau, C., et al., 2022. Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience, 16: 873935.
C. Ostrau, et al., “Benchmarking Neuromorphic Hardware and Its Energy Expenditure”, Frontiers in Neuroscience, vol. 16, 2022, : 873935.
Ostrau, C., Klarhorst, C., Thies, M., Rückert, U.: Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience. 16, : 873935 (2022).
Ostrau, Christoph, Klarhorst, Christian, Thies, Michael, and Rückert, Ulrich. “Benchmarking Neuromorphic Hardware and Its Energy Expenditure”. Frontiers in Neuroscience 16 (2022): 873935.
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