{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:05:14Z","timestamp":1750309514561,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,6,23]],"date-time":"2024-06-23T00:00:00Z","timestamp":1719100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","award":["GRF16213422"],"award-info":[{"award-number":["GRF16213422"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"name":"AI Chip Center for Emerging Smart Systems (ACCESS)"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,6,23]]},"DOI":"10.1145\/3649329.3657391","type":"proceedings-article","created":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T19:27:22Z","timestamp":1731007642000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NAS"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4491-5440","authenticated-orcid":false,"given":"Afzal","family":"Ahmad","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3007-4890","authenticated-orcid":false,"given":"Linfeng","family":"Du","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Kowloon, Hong Kong Special Administrative Region of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4442-592X","authenticated-orcid":false,"given":"Zhiyao","family":"Xie","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7622-6714","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,11,7]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proxylessnas: Direct neural architecture search on target task and hardware. arXiv:1812.00332","author":"Cai Han","year":"2018","unstructured":"Han Cai, Ligeng Zhu, and Song Han. 2018. Proxylessnas: Direct neural architecture search on target task and hardware. arXiv:1812.00332 (2018)."},{"key":"e_1_3_2_1_2_1","volume-title":"A downsampled variant of imagenet as an alternative to the cifar datasets. arXiv preprint arXiv:1707.08819","author":"Chrabaszcz Patryk","year":"2017","unstructured":"Patryk Chrabaszcz, Ilya Loshchilov, and Frank Hutter. 2017. A downsampled variant of imagenet as an alternative to the cifar datasets. arXiv preprint arXiv:1707.08819 (2017)."},{"key":"e_1_3_2_1_3_1","volume-title":"Nas-bench-201: Extending the scope of reproducible neural architecture search. arXiv preprint arXiv:2001.00326","author":"Dong Xuanyi","year":"2020","unstructured":"Xuanyi Dong and Yi Yang. 2020. Nas-bench-201: Extending the scope of reproducible neural architecture search. arXiv preprint arXiv:2001.00326 (2020)."},{"key":"e_1_3_2_1_4_1","first-page":"10480","article-title":"Brp-nas: Prediction-based nas using gcns","volume":"33","author":"Dudziak Lukasz","year":"2020","unstructured":"Lukasz Dudziak, Thomas Chau, Mohamed Abdelfattah, Royson Lee, Hyeji Kim, and Nicholas Lane. 2020. Brp-nas: Prediction-based nas using gcns. Advances in Neural Information Processing Systems 33 (2020), 10480--10490.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_5_1","volume-title":"Accelerator-aware neural network design using automl. arXiv preprint arXiv:2003.02838","author":"Gupta Suyog","year":"2020","unstructured":"Suyog Gupta and Berkin Akin. 2020. Accelerator-aware neural network design using automl. arXiv preprint arXiv:2003.02838 (2020)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Andrew Howard Mark Sandler Grace Chu Liang-Chieh Chen Bo Chen Mingxing Tan Weijun Wang Yukun Zhu Ruoming Pang Vijay Vasudevan et al. 2019. Searching for mobilenetv3. In ICCV.","DOI":"10.1109\/ICCV.2019.00140"},{"key":"e_1_3_2_1_7_1","volume-title":"Progressive growing of gans for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196","author":"Karras Tero","year":"2017","unstructured":"Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen. 2017. Progressive growing of gans for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196 (2017)."},{"key":"e_1_3_2_1_8_1","unstructured":"R. Krishna G. Hinton et al. 2009. CIFAR-10 dataset. https:\/\/www.cs.toronto.edu\/~kriz\/cifar.html."},{"key":"e_1_3_2_1_9_1","volume-title":"Hw-nas-bench: Hardware-aware neural architecture search benchmark. arXiv preprint arXiv:2103.10584","author":"Li Chaojian","year":"2021","unstructured":"Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, and Yingyan Lin. 2021. Hw-nas-bench: Hardware-aware neural architecture search benchmark. arXiv preprint arXiv:2103.10584 (2021)."},{"key":"e_1_3_2_1_10_1","unstructured":"Liam Li and Ameet Talwalkar. 2020. Random search and reproducibility for neural architecture search. PMLR."},{"key":"e_1_3_2_1_11_1","first-page":"1","article-title":"SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization","volume":"23","author":"Lindauer Marius","year":"2022","unstructured":"Marius Lindauer, Katharina Eggensperger, Matthias Feurer, Andr\u00e9 Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, Ren\u00e9 Sass, and Frank Hutter. 2022. SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. J. Mach. Learn. Res. 23, 54 (2022), 1--9.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_1_12_1","volume-title":"BOAH: A tool suite for multi-fidelity bayesian optimization & analysis of hyperparameters. arXiv preprint arXiv:1908.06756","author":"Lindauer Marius","year":"2019","unstructured":"Marius Lindauer, Katharina Eggensperger, Matthias Feurer, Andr\u00e9 Biedenkapp, Joshua Marben, Philipp M\u00fcller, and Frank Hutter. 2019. BOAH: A tool suite for multi-fidelity bayesian optimization & analysis of hyperparameters. arXiv preprint arXiv:1908.06756 (2019)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"e_1_3_2_1_14_1","volume-title":"Nas-bench-301 and the case for surrogate benchmarks for neural architecture search. arXiv preprint arXiv:2008.09777","author":"Siems Julien","year":"2020","unstructured":"Julien Siems, Lucas Zimmer, Arber Zela, Jovita Lukasik, Margret Keuper, and Frank Hutter. 2020. Nas-bench-301 and the case for surrogate benchmarks for neural architecture search. arXiv preprint arXiv:2008.09777 (2020)."},{"key":"e_1_3_2_1_15_1","volume-title":"Mnasnet: Platform-aware neural architecture search for mobile. In CVPR.","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, and Quoc V Le. 2019. Mnasnet: Platform-aware neural architecture search for mobile. In CVPR."},{"key":"e_1_3_2_1_16_1","volume-title":"Efficientnet: Rethinking model scaling for convolutional neural networks. In ICML. PMLR.","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan and Quoc Le. 2019. Efficientnet: Rethinking model scaling for convolutional neural networks. In ICML. PMLR."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01298"},{"key":"e_1_3_2_1_18_1","volume-title":"International Conference on Machine Learning. PMLR, 7105--7114","author":"Ying Chris","year":"2019","unstructured":"Chris Ying, Aaron Klein, Eric Christiansen, Esteban Real, Kevin Murphy, and Frank Hutter. 2019. Nas-bench-101: Towards reproducible neural architecture search. In International Conference on Machine Learning. PMLR, 7105--7114."},{"key":"e_1_3_2_1_19_1","volume-title":"Le","author":"Zoph Barret","year":"2017","unstructured":"Barret Zoph and Quoc V. Le. 2017. Neural Architecture Search with Reinforcement Learning. arXiv:1611.01578 (2017)."}],"event":{"name":"DAC '24: 61st ACM\/IEEE Design Automation Conference","sponsor":["SIGDA ACM Special Interest Group on Design Automation","IEEE-CEDA","SIGBED ACM Special Interest Group on Embedded Systems"],"location":"San Francisco CA USA","acronym":"DAC '24"},"container-title":["Proceedings of the 61st ACM\/IEEE Design Automation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3649329.3657391","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3649329.3657391","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:01Z","timestamp":1750295881000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3649329.3657391"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,23]]},"references-count":19,"alternative-id":["10.1145\/3649329.3657391","10.1145\/3649329"],"URL":"https:\/\/doi.org\/10.1145\/3649329.3657391","relation":{},"subject":[],"published":{"date-parts":[[2024,6,23]]},"assertion":[{"value":"2024-11-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}