{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T01:12:31Z","timestamp":1780708351204,"version":"3.54.1"},"reference-count":75,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&#x0026;D Program of China","award":["2020YFB150001"],"award-info":[{"award-number":["2020YFB150001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072018"],"award-info":[{"award-number":["62072018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61502019"],"award-info":[{"award-number":["61502019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732002"],"award-info":[{"award-number":["61732002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SenseTime Research Fund for Young Scholars"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Parallel Distrib. Syst."],"published-print":{"date-parts":[[2021,3,1]]},"DOI":"10.1109\/tpds.2020.3030548","type":"journal-article","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T19:22:58Z","timestamp":1602616978000},"page":"708-727","source":"Crossref","is-referenced-by-count":190,"title":["The Deep Learning Compiler: A Comprehensive Survey"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4115-9072","authenticated-orcid":false,"given":"Mingzhen","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1829-2817","authenticated-orcid":false,"given":"Yi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingxiao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"You","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1101-7927","authenticated-orcid":false,"given":"Hailong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7186-0556","authenticated-orcid":false,"given":"Zhongzhi","family":"Luan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Gan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangwen","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5382-1473","authenticated-orcid":false,"given":"Depei","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378522"},{"key":"ref72","article-title":"Automatic full compilation of Julia programs and ML models to cloud TPUs","author":"fischer","year":"2018"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1137\/141000671"},{"key":"ref70","article-title":"Fashionable modelling with flux","author":"innes","year":"2018"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2878698"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010051815785"},{"key":"ref75","article-title":"Privacy for rescue: A new testimony why privacy is vulnerable in deep models","author":"gao","year":"2019"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1002\/9780470385951"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/2491956.2462176"},{"key":"ref32","article-title":"The deep learning compiler: A comprehensive survey","author":"li","year":"2020"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICESS.2019.8782480"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CGO.2004.1281665"},{"key":"ref37","author":"goodman","year":"2007","journal-title":"JavaScript Bible"},{"key":"ref36","article-title":"MLIR: A compiler infrastructure for the end of Moore's law","author":"lattner","year":"2020"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/567532.567555"},{"key":"ref34","year":"2020"},{"key":"ref60","article-title":"Chameleon: Adaptive code optimization for expedited deep neural network compilation","author":"ahn","year":"2020","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref62","year":"2020"},{"key":"ref61","article-title":"BFloat16 hardware numerics definition","author":"wang","year":"2017"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2817118"},{"key":"ref28","article-title":"Intel nGraph: An intermediate representation, compiler, and executor for deep learning","author":"cyphers","year":"2018"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/2833179.2833183"},{"key":"ref27","article-title":"Glow: Graph lowering compiler techniques for neural networks","author":"rotem","year":"2018"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/11688839_16"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1145\/2254064.2254123"},{"key":"ref29","article-title":"XLA: Tensorflow, compiled","author":"leary","year":"2017","journal-title":"TensorFlow Dev Summit"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1145\/2581122.2544141"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1145\/2737924.2738003"},{"key":"ref69","first-page":"8757","article-title":"Automatic differentiation in ML: Where we are and where we should be going","author":"van merri\u00ebnboer","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref2","author":"forsyth","year":"2002","journal-title":"Computer Vision A Modern Approach"},{"key":"ref1","author":"manning","year":"1999","journal-title":"Foundations of Statistical Natural Language Processing"},{"key":"ref20","year":"2020"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001179"},{"key":"ref21","year":"2020"},{"key":"ref24","year":"2020"},{"key":"ref23","article-title":"Dissecting the graphcore IPU architecture via microbenchmarking","author":"jia","year":"2019"},{"key":"ref26","article-title":"Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions","author":"vasilache","year":"2018"},{"key":"ref25","first-page":"578","article-title":"TVM: An automated end-to-end optimizing compiler for deep learning","author":"chen","year":"2018","journal-title":"Proc 12th USENIX Symp Operating Syst Des Implementation"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240786"},{"key":"ref51","article-title":"FusionStitching: Deep fusion and code generation for tensorflow computations on GPUs","author":"long","year":"2018"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1177011077"},{"key":"ref58","author":"goldberg","year":"1989","journal-title":"Genetic Algorithms in Search Optimization and Machine Learning"},{"key":"ref57","first-page":"1","article-title":"Learned TPU cost model for XLA tensor programs","author":"kaufman","year":"2019","journal-title":"Proc NeurIPS ML Syst Workshop"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/2400682.2400713"},{"key":"ref55","first-page":"1025","article-title":"Optimizing CNN model inference on CPUs","author":"liu","year":"2019","journal-title":"Proc USENIX Annu Tech Conf"},{"key":"ref54","first-page":"44","article-title":"Ordering Chaos: Memory-aware scheduling of irregularly wired neural networks for edge devices","volume":"2","author":"ahn","year":"2020","journal-title":"Proc Conf Syst Mach Learning"},{"key":"ref53","article-title":"Compilers: Principles, techniques, and tools","author":"aho","year":"0"},{"key":"ref52","article-title":"FusionStitching: Boosting execution efficiency of memory intensive computations for DL workloads","author":"long","year":"2019"},{"key":"ref10","first-page":"265","article-title":"TensorFlow: A system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"Proc 12th USENIX Symp Operating Syst Des Implementation"},{"key":"ref11","first-page":"8024","article-title":"PyTorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref40","article-title":"Relay: A high-level compiler for deep learning","author":"roesch","year":"2019"},{"key":"ref12","article-title":"MXNet: A flexible and efficient machine learning library for heterogeneous distributed systems","author":"chen","year":"2015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2945397"},{"key":"ref14","year":"2020"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080246"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/HOTCHIPS.2019.8875654"},{"key":"ref17","article-title":"A11 bionic processor","author":"kingsley-hughes","year":"2017"},{"key":"ref18","year":"2020"},{"key":"ref19","year":"2020"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2712560"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939678"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2018.01.039"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"rumelhart","year":"1986","journal-title":"Nature"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.scico.2007.08.001"},{"key":"ref9","article-title":"Generative adversarial networks","author":"goodfellow","year":"2014"},{"key":"ref46","article-title":"The omega library","author":"kelly","year":"1996"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15582-6_49"},{"key":"ref48","article-title":"PolyLib: A library for manipulating parameterized polyhedra","author":"loechner","year":"1999"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1051\/ro\/1988220302431"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3190508.3190551"},{"key":"ref41","author":"mccarthy","year":"1965","journal-title":"LISP 1 5 Programmer's Manual"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/115372.115320"},{"key":"ref43","first-page":"8757","article-title":"Automatic differentiation in ML: Where we are and where we should be going","author":"van merrienboer","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"}],"container-title":["IEEE Transactions on Parallel and Distributed Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/71\/9218224\/09222299.pdf?arnumber=9222299","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:31Z","timestamp":1652194231000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9222299\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,1]]},"references-count":75,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tpds.2020.3030548","relation":{},"ISSN":["1045-9219","1558-2183","2161-9883"],"issn-type":[{"value":"1045-9219","type":"print"},{"value":"1558-2183","type":"electronic"},{"value":"2161-9883","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,1]]}}}