{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T09:59:07Z","timestamp":1740131947466,"version":"3.37.3"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&#x0026;D Program of China","doi-asserted-by":"publisher","award":["2022ZD0115304"],"award-info":[{"award-number":["2022ZD0115304"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072479","62332021"],"award-info":[{"award-number":["62072479","62332021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Major Program of Guangdong Basic and Applied Research","award":["2019B030302002"],"award-info":[{"award-number":["2019B030302002"]}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2024B1515020011"],"award-info":[{"award-number":["2024B1515020011"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangzhou Science and Technology Projects","award":["202201011388"],"award-info":[{"award-number":["202201011388"]}]},{"name":"Xiaomi Young Talents Program"},{"name":"Pazhou Lab","award":["PZL2023KF0001"],"award-info":[{"award-number":["PZL2023KF0001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/tc.2024.3398424","type":"journal-article","created":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T17:28:30Z","timestamp":1715275710000},"page":"1899-1912","source":"Crossref","is-referenced-by-count":1,"title":["TensorMap: A Deep RL-Based Tensor Mapping Framework for Spatial Accelerators"],"prefix":"10.1109","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3165-873X","authenticated-orcid":false,"given":"Fuyu","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4747-8020","authenticated-orcid":false,"given":"Minghua","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5315-3375","authenticated-orcid":false,"given":"Yutong","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2166-977X","authenticated-orcid":false,"given":"Nong","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080246"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JETCAS.2019.2910232"},{"key":"ref3","article-title":"Tensor core"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref6","first-page":"1","article-title":"CARLA: An open urban driving simulator","volume-title":"Proc. 1st Annu. Conf. Robot Learn.","author":"Dosovitskiy","year":"2017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref8","article-title":"Nvdla deep learning accelerator"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2016.40"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2749469.2750389"},{"key":"ref11","first-page":"265","article-title":"Tensorflow: A system for large-scale machine learning","volume-title":"Proc. 12th USENIX Symp. Oper. Syst. Des. Implementation (OSDI)","author":"Abadi","year":"2016"},{"key":"ref12","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Paszke","year":"2019"},{"article-title":"Cudnn: Efficient primitives for deep learning","year":"2014","author":"Chetlur","key":"ref13"},{"key":"ref14","article-title":"Mkl-dnn"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378508"},{"key":"ref16","first-page":"863","article-title":"Ansor: Generating high-performance tensor programs for deep learning","volume-title":"Proc. 14th USENIX Symp. Oper. Syst. Des. Implementation (OSDI)","author":"Zheng","year":"2020"},{"key":"ref17","first-page":"578","article-title":"TVM: An automated end-to-end optimizing compiler for deep learning","volume-title":"Proc. USENIX Symp. Oper. Syst. Des. Implementation (OSDI)","author":"Chen","year":"2018"},{"key":"ref18","first-page":"3389","article-title":"Learning to optimize tensor programs","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Chen","year":"2018"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA52012.2021.00086"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3470496.3527440"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3445814.3446762"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISPASS.2019.00042"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA52012.2021.00050"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3485137"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3358198"},{"key":"ref26","first-page":"1057","article-title":"Policy gradient methods for reinforcement learning with function approximation,","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Sutton","year":"1999"},{"key":"ref27","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Mnih","year":"2016"},{"article-title":"Proximal policy optimization algorithms","year":"2017","author":"Schulman","key":"ref28"},{"key":"ref29","first-page":"2430","article-title":"Device placement optimization with reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML), PMLR","author":"Mirhoseini","year":"2017"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03544-w"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3466752.3480114"},{"key":"ref32","first-page":"565","article-title":"Reward shaping in episodic reinforcement learning","volume-title":"Proc. 16th Conf. Auton. Agents MultiAgent Syst. (AAMAS)","author":"Grzeundefined","year":"2017"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref35","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Brown","year":"2020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358252"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA53966.2022.00065"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA56546.2023.10071095"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/1375581.1375595"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2400682.2400713"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CGO.2019.8661197"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3453483.3454106"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3433103"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/12\/10592858\/10527402.pdf?arnumber=10527402","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T07:01:43Z","timestamp":1725606103000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10527402\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":44,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tc.2024.3398424","relation":{},"ISSN":["0018-9340","1557-9956","2326-3814"],"issn-type":[{"type":"print","value":"0018-9340"},{"type":"electronic","value":"1557-9956"},{"type":"electronic","value":"2326-3814"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}