{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T15:58:47Z","timestamp":1759334327484,"version":"build-2065373602"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T00:00:00Z","timestamp":1745798400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T00:00:00Z","timestamp":1745798400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,4,28]]},"DOI":"10.1109\/aicas64808.2025.11173102","type":"proceedings-article","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T17:52:35Z","timestamp":1758822755000},"page":"1-5","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing Mixed-Precision DNN Scheduling on Heterogeneous SoCs for Enhanced Robustness and Efficiency"],"prefix":"10.1109","author":[{"given":"Yulong","family":"Song","sequence":"first","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Tao","sequence":"additional","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinlun","family":"Ji","sequence":"additional","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Congyi","family":"Sun","sequence":"additional","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxiang","family":"Fu","sequence":"additional","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University,Nanjing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume-title":"Proc. ICLR","author":"Han","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3583781.3590226"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3297663.3310305"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3489517.3530572"},{"article-title":"Benchmarking neural network robustness to common corruptions and perturbations","volume-title":"Proc. ICLR","author":"Hendrycks","key":"ref5"},{"key":"ref6","article-title":"Examining the Impact of Blur on Recognition by Convolutional Networks","author":"Vasiljevic","year":"2016","journal-title":"ArXiv"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.485"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3400302.3415639"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/LES.2021.3087707"},{"key":"ref11","first-page":"307","article-title":"HetPipe: Enabling large DNN training on (Whimpy) heterogeneous GPU clusters through integration of pipelined model parallelism and data parallelism","volume-title":"Proc. ATC","author":"H. Park"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2019.01.006"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2017.01.002"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-019-02768-y"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/DAC56929.2023.10247951"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3410463.3414671"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/SOCC58585.2023.10256738"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00881"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3394885.3431554"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"volume-title":"NVIDIA Deep Learning Accelerator","year":"2024","key":"ref21"},{"volume-title":"NVIDIA Deep Learning TensorRT Documentation","year":"2024","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"}],"event":{"name":"2025 IEEE 7th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","start":{"date-parts":[[2025,4,28]]},"location":"Bordeaux, France","end":{"date-parts":[[2025,4,30]]}},"container-title":["2025 IEEE 7th International Conference on Artificial Intelligence Circuits and Systems (AICAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11172731\/11173086\/11173102.pdf?arnumber=11173102","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T14:40:28Z","timestamp":1759243228000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11173102\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,28]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/aicas64808.2025.11173102","relation":{},"subject":[],"published":{"date-parts":[[2025,4,28]]}}}