Journal Article

FZJ-2026-00941

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png The neurobench framework for benchmarking neuromorphic computing algorithms and systems

Yik, J. (Corresponding author) ; Van den Berghe, K. ; den Blanken, D. ; Bouhadjar, Y.FZJ* ; Fabre, M.FZJ* ; Hueber, P. ; Ke, W. ; Khoei, M. A. ; Kleyko, D. ; Pacik-Nelson, N. ; Pierro, A. ; Stratmann, P. ; Sun, P. V. ; Tang, G. ; Wang, S. ; Zhou, B. ; Ahmed, S. H.FZJ* ; Vathakkattil Joseph, G. ; Leto, B. ; Micheli, A. ; Mishra, A. K. ; Lenz, G. ; Sun, T. ; Ahmed, Z. ; Akl, M. ; Anderson, B. ; Andreou, A. G. ; Bartolozzi, C. ; Basu, A. ; Bogdan, P. ; Bohte, S. ; Buckley, S. ; Cauwenberghs, G. ; Chicca, E. ; Corradi, F. ; de Croon, G. ; Danielescu, A. ; Daram, A. ; Davies, M. ; Demirag, Y. ; Eshraghian, J. ; Fischer, T. ; Forest, J. ; Fra, V. ; Furber, S. ; Furlong, P. M. ; Gilpin, W. ; Gilra, A. ; Gonzalez, H. A. ; Indiveri, G. ; Joshi, S. ; Karia, V. ; Khacef, L. ; Knight, J. C. ; Kriener, L. ; Kubendran, R. ; Kudithipudi, D. ; Liu, S.-C. ; Liu, Y.-H. ; Ma, H. ; Manohar, R. ; Margarit-Taulé, J. M. ; Mayr, C. ; Michmizos, K. ; Muir, D. R. ; Neftci, E.FZJ* ; Nowotny, T. ; Ottati, F. ; Ozcelikkale, A. ; Panda, P. ; Park, J. ; Payvand, M. ; Pehle, C. ; Petrovici, M. A. ; Posch, C. ; Renner, A.FZJ* ; Sandamirskaya, Y. ; Schaefer, C. J. S. ; van Schaik, A. ; Schemmel, J. ; Schmidgall, S. ; Schuman, C. ; Seo, J.-s. ; Sheik, S. ; Shrestha, S. B. ; Sifalakis, M. ; Sironi, A. ; Stewart, K. ; Stewart, M. ; Stewart, T. C. ; Timcheck, J. ; Tömen, N. ; Urgese, G. ; Verhelst, M. ; Vineyard, C. M. ; Vogginger, B. ; Yousefzadeh, A. ; Zohora, F. T. ; Frenkel, C. ; Reddi, V. J.

2025
Springer Nature

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Please use a persistent id in citations: doi:10.1038/s41467-025-56739-4  doi:10.34734/FZJ-2026-00941

Abstract: Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. This article presents NeuroBench, a benchmark framework for neuromorphic algorithms and systems, which is collaboratively designed from an open community of researchers across industry and academia. NeuroBench introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent and hardware-dependent settings. For latest project updates, visit the project website (neurobench.ai).

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Contributing Institute(s):

1. Neuromorphic Software Eco System (PGI-15)

Research Program(s):

1. 5234 - Emerging NC Architectures (POF4-523) (POF4-523)
2. BMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) (BMBF-16ME0398K)
3. BMBF 16ME0399 - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0399) (BMBF-16ME0399)
4. BMFTR 03ZU2106CB - NeuroSys: Algorithm-Hardware Co-Design (Projekt C) - B (BMBF-03ZU2106CB) (BMBF-03ZU2106CB)

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