{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:03:19Z","timestamp":1750309399667,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T00:00:00Z","timestamp":1722816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1948201","2310170"],"award-info":[{"award-number":["1948201","2310170"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,5]]},"DOI":"10.1145\/3665314.3672292","type":"proceedings-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T19:31:18Z","timestamp":1725910278000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Systolic Array Acceleration of Spiking Neural Networks with Application-Independent Split-Time Temporal Coding"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7370-889X","authenticated-orcid":false,"given":"Jeongjun","family":"Lee","sequence":"first","affiliation":[{"name":"University of California, Santa Barbara, San Jose, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3548-4589","authenticated-orcid":false,"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"University of California, Santa Barbara, Santa Barbara, CA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,9,9]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Deep learning using rectified linear units (relu). arXiv preprint arXiv:1803.08375","author":"Agaraf A. F.","year":"2018","unstructured":"Agaraf, A. F. Deep learning using rectified linear units (relu). arXiv preprint arXiv:1803.08375 (2018)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.781"},{"key":"e_1_3_2_1_3_1","volume-title":"-C. Feature representations for neuromorphic audio spike streams. Frontiers in neuroscience 12","author":"Anumula J.","year":"2018","unstructured":"Anumula, J., Neil, D., Delbruck, T., and Liu, S.-C. Feature representations for neuromorphic audio spike streams. Frontiers in neuroscience 12 (2018), 23."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2018.2789723"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001177"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.08.001"},{"key":"e_1_3_2_1_7_1","volume-title":"Hybrid macro\/micro level backpropagation for training deep spiking neural networks. Advances in neural information processing systems 31","author":"Jin Y.","year":"2018","unstructured":"Jin, Y., Zhang, W., and Li, P. Hybrid macro\/micro level backpropagation for training deep spiking neural networks. Advances in neural information processing systems 31 (2018)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2017.12.005"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358252"},{"key":"e_1_3_2_1_10_1","volume-title":"Cacti 6.0: A tool to model large caches. HP laboratories 27","author":"Muralimanohar N.","year":"2009","unstructured":"Muralimanohar, N., Balasubramonian, R., and Jouffi, N. P. Cacti 6.0: A tool to model large caches. HP laboratories 27 (2009), 28."},{"key":"e_1_3_2_1_11_1","volume-title":"Converting static image datasets to spiking neuromorphic datasets using saccades. Frontiers in neuroscience 9","author":"Orchard G.","year":"2015","unstructured":"Orchard, G., Jayawant, A., Cohen, G. K., and Thakor, N. Converting static image datasets to spiking neuromorphic datasets using saccades. Frontiers in neuroscience 9 (2015), 437."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218689"},{"key":"e_1_3_2_1_13_1","volume-title":"Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32","author":"Paszke A.","year":"2019","unstructured":"Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al. Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_14_1","volume-title":"Scale-sim: Systolic cnn accelerator simulator. arXiv preprint arXiv:1811.02883","author":"Samajdar A.","year":"2018","unstructured":"Samajdar, A., Zhu, Y., Whatmough, P., Mattina, M., and Krishna, T. Scale-sim: Systolic cnn accelerator simulator. arXiv preprint arXiv:1811.02883 (2018)."},{"key":"e_1_3_2_1_15_1","volume-title":"Slayer: Spike layer error reassignment in time. Advances in neural information processing systems 31","author":"Shrestha S. B.","year":"2018","unstructured":"Shrestha, S. B., and Orchard, G. Slayer: Spike layer error reassignment in time. Advances in neural information processing systems 31 (2018)."},{"key":"e_1_3_2_1_16_1","first-page":"12022","article-title":"Temporal spike sequence learning via backpropagation for deep spiking neural networks","volume":"33","author":"Zhang W.","year":"2020","unstructured":"Zhang, W., and Li, P. Temporal spike sequence learning via backpropagation for deep spiking neural networks. Advances in Neural Information Processing Systems 33 (2020), 12022--12033.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533726"}],"event":{"name":"ISLPED '24: 29th ACM\/IEEE International Symposium on Low Power Electronics and Design","sponsor":["SIGDA ACM Special Interest Group on Design Automation","IEEE CAS","IEEE EDA"],"location":"Newport Beach CA USA","acronym":"ISLPED '24"},"container-title":["Proceedings of the 29th ACM\/IEEE International Symposium on Low Power Electronics and Design"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3665314.3672292","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3665314.3672292","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3665314.3672292","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:57:51Z","timestamp":1750294671000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3665314.3672292"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,5]]},"references-count":17,"alternative-id":["10.1145\/3665314.3672292","10.1145\/3665314"],"URL":"https:\/\/doi.org\/10.1145\/3665314.3672292","relation":{},"subject":[],"published":{"date-parts":[[2024,8,5]]},"assertion":[{"value":"2024-09-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}