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Joao Ambrosi, Aayush Ankit, et al. \"Hardware-software co-design for an analog-digital accelerator for machine learning\". In: 2018 IEEE International Conference on Rebooting Computing (ICRC). IEEE. 2018, pp. 1--13."},{"key":"e_1_3_2_1_4_1","volume-title":"Izzat El Hajj, et al","author":"Ankit Aayush","year":"2019","unstructured":"Aayush Ankit , Izzat El Hajj, et al . PANTHER : A Programmable Architecture for Neural Network Training Harnessing Energyefficient ReRAM. 2019 . arXiv: 1912.11516 [cs.DC]. Aayush Ankit, Izzat El Hajj, et al. PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energyefficient ReRAM. 2019. arXiv: 1912.11516 [cs.DC]."},{"key":"e_1_3_2_1_5_1","first-page":"715731","volume-title":"Proceedings of the TwentyFourth International Conference on Architectural Support for Programming Languages and Operating Systems.","author":"Ankit Aayush","year":"2019","unstructured":"Aayush Ankit , Izzat El Hajj , : A programmable ultraefficient memristorbased accelerator for machine learning inference \". In: Proceedings of the TwentyFourth International Conference on Architectural Support for Programming Languages and Operating Systems. 2019 , p. 715731 . Aayush Ankit, Izzat El Hajj, et al. \"PUMA: A programmable ultraefficient memristorbased accelerator for machine learning inference\". In: Proceedings of the TwentyFourth International Conference on Architectural Support for Programming Languages and Operating Systems. 2019, p. 715731."},{"key":"e_1_3_2_1_6_1","volume-title":"ONNX: Open Neural Network Exchange\". In: arXiv preprint arXiv:1909.11671","author":"Bai H.","year":"2019","unstructured":"H. Bai , J. Cheng , \" ONNX: Open Neural Network Exchange\". In: arXiv preprint arXiv:1909.11671 ( 2019 ). H. Bai, J. Cheng, et al. \"ONNX: Open Neural Network Exchange\". In: arXiv preprint arXiv:1909.11671 (2019)."},{"key":"e_1_3_2_1_7_1","volume-title":"JAX: composable transformations of Python+NumPy programs. https:\/\/github.com\/google\/jax","author":"Bradbury James","year":"2018","unstructured":"James Bradbury , Roy Frostig , JAX: composable transformations of Python+NumPy programs. https:\/\/github.com\/google\/jax . 2018 . James Bradbury, Roy Frostig, et al. JAX: composable transformations of Python+NumPy programs. https:\/\/github.com\/google\/jax. 2018."},{"key":"e_1_3_2_1_8_1","volume-title":"IEEE International Electron Devices Meeting.","author":"B\u00fcchel Julian","year":"2022","unstructured":"Julian B\u00fcchel , A Vasilopoulos , descent-based programming of analog in-memory computing cores \". In: IEEE International Electron Devices Meeting. 2022 . Julian B\u00fcchel, A Vasilopoulos, et al. \"Gradient descent-based programming of analog in-memory computing cores\". In: IEEE International Electron Devices Meeting. 2022."},{"key":"e_1_3_2_1_9_1","first-page":"578","volume-title":"Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI).","author":"Chen Tianqi","year":"2018","unstructured":"Tianqi Chen , Thierry Moreau , : An Automated End-to-End Optimizing Compiler for Deep Learning \". In: Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI). 2018 , pp. 578 -- 594 . Tianqi Chen, Thierry Moreau, et al. \"TVM: An Automated End-to-End Optimizing Compiler for Deep Learning\". In: Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI). 2018, pp. 578--594."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_10_1","DOI":"10.1016\/j.suscom.2021.100520"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_11_1","DOI":"10.1109\/MM.2018.112130359"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_12_1","DOI":"10.3389\/neuro.11.011.2008"},{"key":"e_1_3_2_1_13_1","volume-title":"Training spiking neural networks using lessons from deep learning\". In: arXiv preprint arXiv:2109.12894","author":"Eshraghian Jason K","year":"2021","unstructured":"Jason K Eshraghian , Max Ward , \" Training spiking neural networks using lessons from deep learning\". In: arXiv preprint arXiv:2109.12894 ( 2021 ). 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Steve B Furber, David R Lester, et al. \"SpiNNaker: A multi-core system-on-chip for massively-parallel neural net simulation\". In: IEEE Transactions on Computers 63.2 (2014), pp. 245--259.","journal-title":"IEEE Transactions on Computers"},{"unstructured":"Manash Goswami. Announcing accelerated training with ONNX Runtime\u00e2train models up to 45% faster - Microsoft Open Source Blog. https:\/\/cloudblogs.microsoft.com\/opensource\/2020\/05\/19\/announcing-support-for-accelerated-training-with-onnx-runtime\/. [Online; accessed 07.10.2022]. 2020.  Manash Goswami. Announcing accelerated training with ONNX Runtime\u00e2train models up to 45% faster - Microsoft Open Source Blog. https:\/\/cloudblogs.microsoft.com\/opensource\/2020\/05\/19\/announcing-support-for-accelerated-training-with-onnx-runtime\/. 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[Online; accessed 07.10.2022]. 2015.","key":"e_1_3_2_1_19_1"},{"issue":"2","key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","first-page":"023003","DOI":"10.1088\/1361-6463\/aae223","article-title":"Memristor devices for neural networks","volume":"52","author":"Jeong Hongsik","year":"2018","unstructured":"Hongsik Jeong and Luping Shi . \" Memristor devices for neural networks \". In: Journal of Physics D: Applied Physics 52 . 2 ( 2018 ), p. 023003 . Hongsik Jeong and Luping Shi. \"Memristor devices for neural networks\". In: Journal of Physics D: Applied Physics 52.2 (2018), p. 023003.","journal-title":"Journal of Physics D: Applied Physics"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_21_1","DOI":"10.1145\/3079856.3080246"},{"key":"e_1_3_2_1_22_1","volume-title":"et al","author":"Kong Qiuqiang","year":"2023","unstructured":"Qiuqiang Kong , Yong Xu , et al . Sinabs : A Python Library for Sound Event Detection . https:\/\/sinabs.readthedocs.io\/en\/v1.2.4\/. 2023 . 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In: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems. ACM. 2019 , pp. 15 -- 29 . Xian Luo, Xiaochen Wu, et al. \"Intelligence Processing Unit: When Cloud AI Meets Edge Computing\". In: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems. ACM. 2019, pp. 15--29."},{"key":"e_1_3_2_1_28_1","volume-title":"Spinnaker 2: A 10 million core processor system for brain simulation and machine learning\". In: arXiv preprint arXiv:1911.02385","author":"Mayr Christian","year":"2019","unstructured":"Christian Mayr , Sebastian Hoeppner , \" Spinnaker 2: A 10 million core processor system for brain simulation and machine learning\". In: arXiv preprint arXiv:1911.02385 ( 2019 ). Christian Mayr, Sebastian Hoeppner, et al. \"Spinnaker 2: A 10 million core processor system for brain simulation and machine learning\". In: arXiv preprint arXiv:1911.02385 (2019)."},{"key":"e_1_3_2_1_29_1","first-page":"02385","article-title":"SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning","author":"Mayr Christian","year":"1911","unstructured":"Christian Mayr , Sebastian H\u00f6ppner , \" SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning \". In: CoRR abs\/ 1911 . 02385 (2019). arXiv: 1911.02385. url: http:\/\/arxiv.org\/abs\/1911.02385. Christian Mayr, Sebastian H\u00f6ppner, et al. \"SpiNNaker 2: A 10 Million Core Processor System for Brain Simulation and Machine Learning\". In: CoRR abs\/1911.02385 (2019). arXiv: 1911.02385. url: http:\/\/arxiv.org\/abs\/1911.02385.","journal-title":"CoRR abs\/"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_30_1","DOI":"10.1109\/tbcas.2021.3089622"},{"key":"e_1_3_2_1_31_1","first-page":"106","volume-title":"IEEE transactions on biomedical circuits and systems 12.1","author":"Moradi Saber","year":"2017","unstructured":"Saber Moradi , Ning Qiao , \" A scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors (DYNAPs) \". In: IEEE transactions on biomedical circuits and systems 12.1 ( 2017 ), pp. 106 -- 122 . Saber Moradi, Ning Qiao, et al. \"A scalable multicore architecture with heterogeneous memory structures for dynamic neuromorphic asynchronous processors (DYNAPs)\". In: IEEE transactions on biomedical circuits and systems 12.1 (2017), pp. 106--122."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_32_1","DOI":"10.5281\/zenodo.3773845"},{"key":"e_1_3_2_1_33_1","volume-title":"Extending brainscales OS for BrainScaleS-2\". In: arXiv preprint arXiv:2003.13750","author":"M\u00fcller Eric","year":"2020","unstructured":"Eric M\u00fcller , Christian Mauch , \" Extending brainscales OS for BrainScaleS-2\". In: arXiv preprint arXiv:2003.13750 ( 2020 ). Eric M\u00fcller, Christian Mauch, et al. \"Extending brainscales OS for BrainScaleS-2\". In: arXiv preprint arXiv:2003.13750 (2020)."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_34_1","DOI":"10.1016\/j.vlsi.2011.03.003"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_35_1","DOI":"10.1109\/MSP.2019.2931595"},{"key":"e_1_3_2_1_36_1","first-page":"2111","author":"Orchard Garrick","year":"2021","unstructured":"Garrick Orchard , E. Paxon Frady , . Efficient Neuromorphic Signal Processing with Loihi 2. 2021 . arXiv: 2111 .03746 [cs.ET]. Garrick Orchard, E. Paxon Frady, et al. Efficient Neuromorphic Signal Processing with Loihi 2. 2021. arXiv: 2111.03746 [cs.ET].","journal-title":"Efficient Neuromorphic Signal Processing with Loihi 2."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_37_1","DOI":"10.1109\/JSSC.2013.2259038"},{"key":"e_1_3_2_1_38_1","volume-title":"PyTorch: An Imperative Style","author":"Paszke Adam","year":"1912","unstructured":"Adam Paszke , Sam Gross , PyTorch: An Imperative Style , High-Performance Deep Learning Library . https:\/\/arxiv.org\/abs\/ 1912 .01703. arXiv:1912.01703 [cs.LG]. 2019. Adam Paszke, Sam Gross, et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library. https:\/\/arxiv.org\/abs\/1912.01703. arXiv:1912.01703 [cs.LG]. 2019."},{"key":"e_1_3_2_1_39_1","first-page":"2201","article-title":"The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity","volume":"11063","author":"Pehle Christian","year":"2022","unstructured":"Christian Pehle , Sebastian Billaudelle , \" The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity \". In: CoRR abs\/2201 . 11063 ( 2022 ). arXiv: 2201 .11063. url: https:\/\/arxiv.org\/abs\/2201.11063. Christian Pehle, Sebastian Billaudelle, et al. \"The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity\". In: CoRR abs\/2201.11063 (2022). arXiv: 2201.11063. url: https:\/\/arxiv.org\/abs\/2201.11063.","journal-title":"CoRR abs\/2201"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_40_1","DOI":"10.5281\/zenodo.4422025"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_41_1","DOI":"10.1038\/nature14441"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_42_1","DOI":"10.1109\/AICAS51828.2021.9458494"},{"key":"e_1_3_2_1_43_1","volume-title":"et al. Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline","author":"Richter Ole","year":"2023","unstructured":"Ole Richter , Yannan Xing , et al. Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline . 2023 . arXiv: 2304.06793 [cs.NE]. Ole Richter, Yannan Xing, et al. Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline. 2023. arXiv: 2304.06793 [cs.NE]."},{"key":"e_1_3_2_1_44_1","volume-title":"Compiling machine learning for peak performance\". In","author":"Sabne Amit","year":"2020","unstructured":"Amit Sabne . \"Xla : Compiling machine learning for peak performance\". In : ( 2020 ). Amit Sabne. \"Xla: Compiling machine learning for peak performance\". In: (2020)."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_45_1","DOI":"10.1109\/ISCA.2016.12"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_46_1","DOI":"10.1145\/3584954.3584993"},{"key":"e_1_3_2_1_47_1","volume-title":"IoT Streams for DataDriven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning","author":"Spilger Philipp","year":"2020","unstructured":"Philipp Spilger , Eric M\u00fcller , \" hxtorch: PyTorch for BrainScaleS2 \". In: IoT Streams for DataDriven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning . Springer , 2020 , p. 189200. Philipp Spilger, Eric M\u00fcller, et al. \"hxtorch: PyTorch for BrainScaleS2\". In: IoT Streams for DataDriven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning. Springer, 2020, p. 189200."},{"key":"e_1_3_2_1_48_1","volume-title":"Christophe De Wagter, et al. Neuromorphic Control using Input-Weighted Threshold Adaptation","author":"Stroobants Stein","year":"2023","unstructured":"Stein Stroobants , Christophe De Wagter, et al. Neuromorphic Control using Input-Weighted Threshold Adaptation . 2023 . arXiv: 2304.08778 [cs.RO]. Stein Stroobants, Christophe De Wagter, et al. Neuromorphic Control using Input-Weighted Threshold Adaptation. 2023. arXiv: 2304.08778 [cs.RO]."},{"volume-title":"SAMNA: Synsense Artificial Neural Network Architecture. https:\/\/synsense-sys-int.gitlab.io\/samna\/","year":"2023","unstructured":"Synsense. SAMNA: Synsense Artificial Neural Network Architecture. https:\/\/synsense-sys-int.gitlab.io\/samna\/ . 2023 . Synsense. SAMNA: Synsense Artificial Neural Network Architecture. https:\/\/synsense-sys-int.gitlab.io\/samna\/. 2023.","key":"e_1_3_2_1_49_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_50_1","DOI":"10.1038\/s41928-019-0221-6"},{"key":"e_1_3_2_1_51_1","volume-title":"Soikat Hasan Ahmed, et al. NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking","author":"Yik Jason","year":"2023","unstructured":"Jason Yik , Soikat Hasan Ahmed, et al. NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking . 2023 . arXiv: 2304.04640 [cs.AI]. Jason Yik, Soikat Hasan Ahmed, et al. 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