The neurobench framework for benchmarking neuromorphic computing algorithms and systems

• Published in: Nature communications Vol. 16; no. 1; pp. 1545 - 24
• Main Authors: Yik, Jason, Van den Berghe, Korneel, den Blanken, Douwe, Bouhadjar, Younes, Fabre, Maxime, Hueber, Paul, Ke, Weijie, Khoei, Mina A, Kleyko, Denis, Pacik-Nelson, Noah, Pierro, Alessandro, Stratmann, Philipp, Sun, Pao-Sheng Vincent, Tang, Guangzhi, Wang, Shenqi, Zhou, Biyan, Ahmed, Soikat Hasan, Vathakkattil Joseph, George, Leto, Benedetto, Micheli, Aurora, Mishra, Anurag Kumar, Lenz, Gregor, Sun, Tao, Ahmed, Zergham, Akl, Mahmoud, Anderson, Brian, Andreou, Andreas G, Bartolozzi, Chiara, Basu, Arindam, Bogdan, Petrut, Bohte, Sander, Buckley, Sonia, Cauwenberghs, Gert, Chicca, Elisabetta, Corradi, Federico, de Croon, Guido, Danielescu, Andreea, Daram, Anurag, Davies, Mike, Demirag, Yigit, Eshraghian, Jason, Fischer, Tobias, Forest, Jeremy, Fra, Vittorio, Furber, Steve, Furlong, P. Michael, Gilpin, William, Gilra, Aditya, Gonzalez, Hector A, Indiveri, Giacomo, Joshi, Siddharth, Karia, Vedant, Khacef, Lyes, Knight, James C, Kriener, Laura, Kubendran, Rajkumar, Kudithipudi, Dhireesha, Liu, Shih-Chii, Liu, Yao-Hong, Ma, Haoyuan, Manohar, Rajit, Margarit-Taulé, Josep Maria, Mayr, Christian, Michmizos, Konstantinos, Muir, Dylan R, Neftci, Emre, Nowotny, Thomas, Ottati, Fabrizio, Ozcelikkale, Ayca, Panda, Priyadarshini, Park, Jongkil, Payvand, Melika, Pehle, Christian, Petrovici, Mihai A, Posch, Christoph, Renner, Alpha, Sandamirskaya, Yulia, Schaefer, Clemens J. S, van Schaik, André, Schemmel, Johannes, Schmidgall, Samuel, Schuman, Catherine, Seo, Jae-sun, Sheik, Sadique, Shrestha, Sumit Bam, Sifalakis, Manolis, Sironi, Amos, Stewart, Kenneth, Stewart, Matthew, Stewart, Terrence C, Timcheck, Jonathan, Tömen, Nergis, Urgese, Gianvito, Verhelst, Marian, Vineyard, Craig M, Vogginger, Bernhard, Yousefzadeh, Amirreza, Zohora, Fatima Tuz, Frenkel, Charlotte, Reddi, Vijay Janapa
• Format: Journal Article
• Language: English
• Published: London Springer Nature 11.02.2025; Nature Publishing Group UK; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/117; 639/705/794; Algorithms; Artificial intelligence; Benchmarks; Brain; Brain research; Business metrics; computer science; Energy efficiency; Hardware; Humanities and Social Sciences; multidisciplinary; Neuromorphic computing; Perspective; Physics; Science; Science (multidisciplinary); software; technological development; benchmarking; academia; controlled study; accuracy assessment; review; performance assessment; diagnosis; artificial intelligence software; algorithm; hardware
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-025-56739-4

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).
NRC publication: Yes