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@ARTICLE{Yik:1024854,
      author       = {Yik, Jason and Berghe, Korneel Van den and Blanken, Douwe
                      den and Bouhadjar, Younes and Fabre, Maxime and Hueber, Paul
                      and Kleyko, Denis and Pacik-Nelson, Noah and Sun, Pao-Sheng
                      Vincent and Tang, Guangzhi and Wang, Shenqi and Zhou, Biyan
                      and Ahmed, Soikat Hasan and Joseph, George Vathakkattil and
                      Leto, Benedetto and Micheli, Aurora and Mishra, Anurag Kumar
                      and Lenz, Gregor and Sun, Tao and Ahmed, Zergham and Akl,
                      Mahmoud and Anderson, Brian and Andreou, Andreas G. and
                      Bartolozzi, Chiara and Basu, Arindam and Bogdan, Petrut and
                      Bohte, Sander and Buckley, Sonia and Cauwenberghs, Gert and
                      Chicca, Elisabetta and Corradi, Federico and de Croon, Guido
                      and Danielescu, Andreea and Daram, Anurag and Davies, Mike
                      and Demirag, Yigit and Eshraghian, Jason and Fischer, Tobias
                      and Forest, Jeremy and Fra, Vittorio and Furber, Steve and
                      Furlong, P. Michael and Gilpin, William and Gilra, Aditya
                      and Gonzalez, Hector A. and Indiveri, Giacomo and Joshi,
                      Siddharth and Karia, Vedant and Khacef, Lyes and Knight,
                      James C. and Kriener, Laura and Kubendran, Rajkumar and
                      Kudithipudi, Dhireesha and Liu, Yao-Hong and Liu, Shih-Chii
                      and Ma, Haoyuan and Manohar, Rajit and Margarit-Taulé,
                      Josep Maria and Mayr, Christian and Michmizos, Konstantinos
                      and Muir, Dylan and Neftci, Emre and Nowotny, Thomas and
                      Ottati, Fabrizio and Ozcelikkale, Ayca and Panda,
                      Priyadarshini and Park, Jongkil and Payvand, Melika and
                      Pehle, Christian and Petrovici, Mihai A. and Pierro,
                      Alessandro and Posch, Christoph and Renner, Alpha and
                      Sandamirskaya, Yulia and Schaefer, Clemens JS and van
                      Schaik, André and Schemmel, Johannes and Schmidgall, Samuel
                      and Schuman, Catherine and Seo, Jae-sun and Sheik, Sadique
                      and Shrestha, Sumit Bam and Sifalakis, Manolis and Sironi,
                      Amos and Stewart, Matthew and Stewart, Kenneth and Stewart,
                      Terrence C. and Stratmann, Philipp and Timcheck, Jonathan
                      and Tömen, Nergis and Urgese, Gianvito and Verhelst, Marian
                      and Vineyard, Craig M. and Vogginger, Bernhard and
                      Yousefzadeh, Amirreza and Zohora, Fatima Tuz and Frenkel,
                      Charlotte and Reddi, Vijay Janapa},
      title        = {{N}euro{B}ench: {A} {F}ramework for {B}enchmarking
                      {N}euromorphic {C}omputing {A}lgorithms and {S}ystems},
      publisher    = {arXiv},
      reportid     = {FZJ-2024-02520},
      year         = {2023},
      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. Prior
                      neuromorphic computing benchmark efforts have not seen
                      widespread adoption due to a lack of inclusive, actionable,
                      and iterative benchmark design and guidelines. To address
                      these shortcomings, we present NeuroBench: a benchmark
                      framework for neuromorphic computing algorithms and systems.
                      NeuroBench is a collaboratively-designed effort from an open
                      community of nearly 100 co-authors across over 50
                      institutions in industry and academia, aiming to provide a
                      representative structure for standardizing the evaluation of
                      neuromorphic approaches. The NeuroBench framework 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 (algorithm track) and
                      hardware-dependent (system track) settings. In this article,
                      we present initial performance baselines across various
                      model architectures on the algorithm track and outline the
                      system track benchmark tasks and guidelines. NeuroBench is
                      intended to continually expand its benchmarks and features
                      to foster and track the progress made by the research
                      community.},
      keywords     = {Artificial Intelligence (cs.AI) (Other) / FOS: Computer and
                      information sciences (Other)},
      cin          = {PGI-15},
      cid          = {I:(DE-Juel1)PGI-15-20210701},
      pnm          = {5234 - Emerging NC Architectures (POF4-523)},
      pid          = {G:(DE-HGF)POF4-5234},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/ARXIV.2304.04640},
      url          = {https://juser.fz-juelich.de/record/1024854},
}