{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T01:42:29Z","timestamp":1787017349968,"version":"build-2736575974"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T00:00:00Z","timestamp":1695254400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Cluster of Excellence ?Centre for Tactile Internet with Human-in-the-Loop? (CeTI)","award":["390696704"],"award-info":[{"award-number":["390696704"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,9,21]]},"DOI":"10.1145\/3615338.3618125","type":"proceedings-article","created":{"date-parts":[[2024,6,10]],"date-time":"2024-06-10T08:43:58Z","timestamp":1718009038000},"page":"37-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3288-9516","authenticated-orcid":false,"given":"Chen","family":"Liu","sequence":"first","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3147-1625","authenticated-orcid":false,"given":"Matthias","family":"Jobst","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7170-0464","authenticated-orcid":false,"given":"Liyuan","family":"Guo","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8102-7614","authenticated-orcid":false,"given":"Xinyue","family":"Shi","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6286-5064","authenticated-orcid":false,"given":"Johannes","family":"Partzsch","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3502-0872","authenticated-orcid":false,"given":"Christian","family":"Mayr","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,6,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2155555.2155569"},{"key":"e_1_3_2_1_2_1","volume-title":"Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Tiezhen Wang, Pete Warden, and Rocky Rhodes.","author":"David Robert","year":"2021","unstructured":"Robert David, Jared Duke, Advait Jain, Vijay Janapa Reddi, Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Tiezhen Wang, Pete Warden, and Rocky Rhodes. 2021. TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems. In Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.), Vol. 3. 800--811. https:\/\/proceedings.mlsys.org\/paper\/2021\/file\/d2ddea18f00665ce8623e36bd4e3c7c5-Paper.pdf"},{"key":"e_1_3_2_1_3_1","unstructured":"Sebastian H\u00f6ppner Yexin Yan Andreas Dixius Stefan Scholze Johannes Partzsch Marco Stolba Florian Kelber Bernhard Vogginger Felix Neum\u00e4rker Georg Ellguth et al. 2021. The SpiNNaker 2 processing element architecture for hybrid digital neuromorphic computing. arXiv:2103.08392"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/AICAS54282.2022.9869958"},{"key":"e_1_3_2_1_5_1","volume-title":"Adam: A method for stochastic optimization. arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv:1412.6980"},{"key":"e_1_3_2_1_6_1","volume-title":"Retrieved","author":"Klaiber Michael J.","year":"2022","unstructured":"Michael J. Klaiber, Paul Palomero Bernardo, and Christoph Gerum. 2022. UMA: Universal Modular Accelerator Interface. Retrieved September, 2022 from https:\/\/tvm.apache.org\/docs\/reference\/langref\/relay_op.html"},{"key":"e_1_3_2_1_7_1","volume-title":"Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus. arXiv:1801.06601","author":"Lai Liangzhen","year":"2018","unstructured":"Liangzhen Lai, Naveen Suda, and Vikas Chandra. 2018. Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus. arXiv:1801.06601"},{"key":"e_1_3_2_1_8_1","volume-title":"Retrieved","author":"Team VINO","year":"2018","unstructured":"OpenVINO Team. 2018. OpenVINO. Retrieved April, 2022 from https:\/\/github.com\/openvinotoolkit\/openvino"},{"key":"e_1_3_2_1_9_1","volume-title":"Retrieved","author":"Glow Team PyTorch","year":"2022","unstructured":"PyTorch Glow Team. 2022. PyTorch Glow. Retrieved April, 2022 from https:\/\/github.com\/pytorch\/glow"},{"key":"e_1_3_2_1_10_1","volume-title":"Retrieved","author":"Lite Team TensorFlow","year":"2020","unstructured":"TensorFlow Lite Team. 2020. TensorFlow Lite. Retrieved April, 2022 from https:\/\/www.tensorflow.org\/lite\/"},{"key":"e_1_3_2_1_11_1","volume-title":"Retrieved","author":"Team TVM","year":"2018","unstructured":"TVM Team. 2018. TVM. Retrieved August, 2022 from https:\/\/github.com\/apache\/tvm"},{"key":"e_1_3_2_1_12_1","volume-title":"Retrieved","author":"Team TVM","year":"2022","unstructured":"TVM Team. 2022. Adding an Operator to Relay. Retrieved April, 2022 from https:\/\/tvm.apache.org\/docs\/dev\/how_to\/relay_add_op.html"},{"key":"e_1_3_2_1_13_1","volume-title":"Retrieved","author":"Team TVM","year":"2022","unstructured":"TVM Team. 2022. Relay Core Tensor Operators. Retrieved April, 2022 from https:\/\/tvm.apache.org\/docs\/reference\/langref\/relay_op.html"},{"key":"e_1_3_2_1_14_1","volume-title":"Retrieved","author":"Team TVM","year":"2022","unstructured":"TVM Team. 2022. Relay Operator Strategy. Retrieved April, 2022 from https:\/\/tvm.apache.org\/docs\/\/arch\/relay_op_strategy.html"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.4028\/p-5zh70u"}],"event":{"name":"CODAI '23: 2023 Workshop on Compilers, Deployment, and Tooling for Edge AI","location":"Hamburg Germany","acronym":"CODAI '23","sponsor":["SIGBED ACM Special Interest Group on Embedded Systems","SIGDA ACM Special Interest Group on Design Automation","SIGMICRO ACM Special Interest Group on Microarchitectural Research and Processing","CEDA","IEEE CAS"]},"container-title":["Proceedings of the 2023 Workshop on Compilers, Deployment, and Tooling for Edge AI"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3615338.3618125","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3615338.3618125","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T12:36:53Z","timestamp":1750163813000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3615338.3618125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,21]]},"references-count":15,"alternative-id":["10.1145\/3615338.3618125","10.1145\/3615338"],"URL":"https:\/\/doi.org\/10.1145\/3615338.3618125","relation":{},"subject":[],"published":{"date-parts":[[2023,9,21]]},"assertion":[{"value":"2024-06-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}