{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:36:59Z","timestamp":1773247019901,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":53,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&D Program of China","award":["2023YFB4503204"],"award-info":[{"award-number":["2023YFB4503204"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1145\/3696443.3708924","type":"proceedings-article","created":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T11:50:26Z","timestamp":1740225026000},"page":"193-208","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["ANT-ACE: An FHE Compiler Framework for Automating Neural Network Inference"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2098-2193","authenticated-orcid":false,"given":"Long","family":"Li","sequence":"first","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5782-0454","authenticated-orcid":false,"given":"Jianxin","family":"Lai","sequence":"additional","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7070-6828","authenticated-orcid":false,"given":"Peng","family":"Yuan","sequence":"additional","affiliation":[{"name":"Ant Group, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9692-5578","authenticated-orcid":false,"given":"Tianxiang","family":"Sui","sequence":"additional","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6845-7864","authenticated-orcid":false,"given":"Yan","family":"Liu","sequence":"additional","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5144-5442","authenticated-orcid":false,"given":"Qing","family":"Zhu","sequence":"additional","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8443-3803","authenticated-orcid":false,"given":"Xiaojing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ant Group, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2778-7100","authenticated-orcid":false,"given":"Linjie","family":"Xiao","sequence":"additional","affiliation":[{"name":"Ant Group, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4281-1018","authenticated-orcid":false,"given":"Wenguang","family":"Chen","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"},{"name":"Ant Group, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0380-3506","authenticated-orcid":false,"given":"Jingling","family":"Xue","sequence":"additional","affiliation":[{"name":"UNSW, Sydney, Australia"},{"name":"Ant Group, Sydney, Australia"}]}],"member":"320","published-online":{"date-parts":[[2025,3]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2021. Getting Started Converting TensorFlow to ONNX. Online:. https:\/\/onnxruntime.ai\/docs\/tutorials\/tf-get-started.html"},{"key":"e_1_3_2_1_2_1","unstructured":"2023. torch.fx. Online:. https:\/\/pytorch.org\/docs\/stable\/fx.html"},{"key":"e_1_3_2_1_3_1","unstructured":"2024. Lattigo v6. Online:. https:\/\/github.com\/tuneinsight\/lattigo EPFL-LDS Tune Insight SA"},{"key":"e_1_3_2_1_4_1","unstructured":"2024. ONNX Operators. Online:. https:\/\/onnx.ai\/onnx\/operators\/index.html"},{"key":"e_1_3_2_1_5_1","unstructured":"2024. ONNX Runtime. Online:. https:\/\/onnxruntime.ai\/"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3560827.3563379"},{"key":"e_1_3_2_1_7_1","unstructured":"Martin R. Albrecht Melissa Chase Hao Chen Jintai Ding Shafi Goldwasser Sergey Gorbunov Shai Halevi Jeffrey Hoffstein Kim Laine Kristin E. Lauter Satya Lokam Daniele Micciancio Dustin Moody Travis Morrison Amit Sahai and Vinod Vaikuntanathan. 2019. Homomorphic Encryption Standard. IACR Cryptol. ePrint Arch. 939. https:\/\/eprint.iacr.org\/2019\/939"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","unstructured":"Song Bian Zian Zhao Zhou Zhang Ran Mao Kohei Suenaga Yier Jin Zhenyu Guan and Jianwei Liu. 2023. HEIR: A Unified Representation for Cross-Scheme Compilation of Fully Homomorphic Computation. Cryptology ePrint Archive Paper 2023\/1445. https:\/\/doi.org\/10.14722\/ndss.2024.23067 10.14722\/ndss.2024.23067","DOI":"10.14722\/ndss.2024.23067"},{"key":"e_1_3_2_1_9_1","volume-title":"nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data. CoRR, abs\/1810.10121","author":"Boemer Fabian","year":"2018","unstructured":"Fabian Boemer, Yixing Lao, and Casimir Wierzynski. 2018. nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data. CoRR, abs\/1810.10121 (2018), arXiv:1810.10121. arxiv:1810.10121"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Jean-Philippe Bossuat Rosario Cammarota Jung Hee Cheon Ilaria Chillotti Benjamin R. Curtis Wei Dai Huijing Gong Erin Hales Duhyeong Kim Bryan Kumara Changmin Lee Xianhui Lu Carsten Maple Alberto Pedrouzo-Ulloa Rachel Player Luis Antonio Ruiz Lopez Yongsoo Song Donggeon Yhee and Bahattin Yildiz. 2024. Security Guidelines for Implementing Homomorphic Encryption. Cryptology ePrint Archive Paper 2024\/463. https:\/\/eprint.iacr.org\/2024\/463","DOI":"10.62056\/anxra69p1"},{"key":"e_1_3_2_1_11_1","unstructured":"Florian Bourse Michele Minelli Matthias Minihold and Pascal Paillier. 2017. Fast Homomorphic Evaluation of Deep Discretized Neural Networks. Cryptology ePrint Archive Paper 2017\/1114. https:\/\/eprint.iacr.org\/2017\/1114"},{"key":"e_1_3_2_1_12_1","unstructured":"Zvika Brakerski Craig Gentry and Vinod Vaikuntanathan. 2011. Fully Homomorphic Encryption without Bootstrapping. Cryptology ePrint Archive Paper 2011\/277. https:\/\/eprint.iacr.org\/2011\/277"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-10970-7_16"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70694-8_15"},{"key":"e_1_3_2_1_15_1","volume-title":"Nektarios Georgios Tsoutsos, and Michail Maniatakos","author":"Chielle Eduardo","year":"2018","unstructured":"Eduardo Chielle, Oleg Mazonka, Homer Gamil, Nektarios Georgios Tsoutsos, and Michail Maniatakos. 2018. E3: A Framework for Compiling C++ Programs with Encrypted Operands. Cryptology ePrint Archive, Report 2018\/1013. https:\/\/ia.cr\/2018\/1013"},{"key":"e_1_3_2_1_16_1","volume-title":"TFHE: Fast Fully Homomorphic Encryption over the Torus. Cryptology ePrint Archive, Paper 2018\/421. https:\/\/eprint.iacr.org\/2018\/421","author":"Chillotti Ilaria","year":"2018","unstructured":"Ilaria Chillotti, Nicolas Gama, Mariya Georgieva, and Malika Izabach\u00e8ne. 2018. TFHE: Fast Fully Homomorphic Encryption over the Torus. Cryptology ePrint Archive, Paper 2018\/421. https:\/\/eprint.iacr.org\/2018\/421"},{"key":"e_1_3_2_1_17_1","unstructured":"Thiago Crepaldi. 2024. Export a PyTorch model to ONNX. Online:. https:\/\/pytorch.org\/tutorials\/beginner\/onnx\/export_simple_model_to_onnx_tutorial.html"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3385412.3386023"},{"key":"e_1_3_2_1_19_1","volume-title":"CHET: An Optimizing Compiler for Fully-Homomorphic Neural-Network Inferencing. In PLDI","author":"Dathathri Roshan","year":"2019","unstructured":"Roshan Dathathri, Olli Saarikivi, Hao Chen, Kim Laine, Kristin Lauter, Saeed Maleki, Madan Musuvathi, and Todd Mytkowicz. 2019. CHET: An Optimizing Compiler for Fully-Homomorphic Neural-Network Inferencing. In PLDI 2019. ACM, 142\u2013156. https:\/\/www.microsoft.com\/en-us\/research\/publication\/chet-an-optimizing-compiler-for-fully-homomorphic-neural-network-inferencing\/"},{"key":"e_1_3_2_1_20_1","unstructured":"Junfeng Fan and Frederik Vercauteren. 2012. Somewhat Practical Fully Homomorphic Encryption. Cryptology ePrint Archive Paper 2012\/144. https:\/\/eprint.iacr.org\/2012\/144"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA56546.2023.10071017"},{"key":"e_1_3_2_1_22_1","volume-title":"A fully homomorphic encryption scheme. Ph. D. Dissertation","author":"Gentry Craig","year":"1834","unstructured":"Craig Gentry. 2009. A fully homomorphic encryption scheme. Ph. D. Dissertation. Stanford University. https:\/\/dl.acm.org\/doi\/10.5555\/1834954"},{"key":"e_1_3_2_1_23_1","unstructured":"Craig Gentry and Shai Halevi. 2010. Implementing Gentry\u2019s Fully-Homomorphic Encryption Scheme. Cryptology ePrint Archive Paper 2010\/520. https:\/\/eprint.iacr.org\/2010\/520"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32009-5_49"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40041-4_5"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2402.07901"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 33nd International Conference on Machine Learning, ICML","author":"Gilad-Bachrach Ran","year":"2016","unstructured":"Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin E. Lauter, Michael Naehrig, and John Wernsing. 2016. CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, Maria-Florina Balcan and Kilian Q. Weinberger (Eds.) (JMLR Workshop and Conference Proceedings, Vol. 48). JMLR.org, 201\u2013210. http:\/\/proceedings.mlr.press\/v48\/gilad-bachrach16.html"},{"key":"e_1_3_2_1_28_1","volume-title":"Yurii Sushko, and Bryant Gipson.","author":"Gorantala Shruthi","year":"2021","unstructured":"Shruthi Gorantala, Rob Springer, Sean Purser-Haskell, William Lam, Royce Wilson, Asra Ali, Eric P. Astor, Itai Zukerman, Sam Ruth, Christoph Dibak, Phillipp Schoppmann, Sasha Kulankhina, Alain Forget, David Marn, Cameron Tew, Rafael Misoczki, Bernat Guillen, Xinyu Ye, Dennis Kraft, Damien Desfontaines, Aishe Krishnamurthy, Miguel Guevara, Irippuge Milinda Perera, Yurii Sushko, and Bryant Gipson. 2021. A General Purpose Transpiler for Fully Homomorphic Encryption. Cryptology ePrint Archive, Paper 2021\/811. https:\/\/eprint.iacr.org\/2021\/811"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","unstructured":"Gamze G\u00fcrsoy Eduardo Chielle Charlotte M. Brannon Michail Maniatakos and Mark Gerstein. 2020. Privacy-preserving genotype imputation with fully homomorphic encryption. bioRxiv https:\/\/doi.org\/10.1101\/2020.05.29.124412 10.1101\/2020.05.29.124412","DOI":"10.1101\/2020.05.29.124412"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44371-2_31"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-40186-3_16"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO56248.2022.00086"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3656382"},{"key":"e_1_3_2_1_34_1","volume-title":"Password Monitor: Safeguarding passwords in Microsoft Edge. Online:. https:\/\/www.microsoft.com\/en-us\/research\/blog\/password-monitor-safeguarding-passwords-in-microsoft-edge\/","author":"Lauter Kristin","year":"2021","unstructured":"Kristin Lauter, Sreekanth Kannepalli, Kim Laine, and Radames Cruz Moreno. 2021. Password Monitor: Safeguarding passwords in Microsoft Edge. Online:. https:\/\/www.microsoft.com\/en-us\/research\/blog\/password-monitor-safeguarding-passwords-in-microsoft-edge\/"},{"key":"e_1_3_2_1_35_1","unstructured":"Eunsang Lee Joon-Woo Lee Junghyun Lee Young-Sik Kim Yongjune Kim Jong-Seon No and Woosuk Choi. 2021. Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions. Cryptology ePrint Archive Paper 2021\/1688. https:\/\/eprint.iacr.org\/2021\/1688"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2021.3105111"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","unstructured":"Long Li. 2024. ANT-ACE: an FHE Compiler Framework. https:\/\/doi.org\/10.5281\/zenodo.14625994 10.5281\/zenodo.14625994","DOI":"10.5281\/zenodo.14625994"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3669940.3707276"},{"key":"e_1_3_2_1_39_1","volume-title":"HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture. arxiv:2106.00038.","author":"Lou Qian","year":"2021","unstructured":"Qian Lou and Lei Jiang. 2021. HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture. arxiv:2106.00038."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.46586\/TCHES.V2023.I2.358-380"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13190-5_1"},{"key":"e_1_3_2_1_42_1","volume-title":"Advanced compiler design and implementation","author":"Muchnick Steven Stanley","unstructured":"Steven Stanley Muchnick. 1998. Advanced compiler design and implementation. Morgan Kaufmann Publishers Inc., 340 Pine Street, Sixth Floor, San Francisco, CA, United States. https:\/\/dl.acm.org\/doi\/10.5555\/286076"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1561\/0400000074"},{"key":"e_1_3_2_1_44_1","unstructured":"Oded Regev. 2024. On Lattices Learning with Errors Random Linear Codes and Cryptography. arxiv:2401.03703."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3466752.3480070"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3470496.3527393"},{"key":"e_1_3_2_1_47_1","volume-title":"https:\/\/github.com\/Microsoft\/SEAL Microsoft Research","author":"Microsoft SEAL","unstructured":"2020. Microsoft SEAL (release 3.6). https:\/\/github.com\/Microsoft\/SEAL Microsoft Research, Redmond, WA."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3315508.3329973"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3576915.3623159"},{"key":"e_1_3_2_1_50_1","volume-title":"HECO: Automatic Code Optimizations for Efficient Fully Homomorphic Encryption. arxiv:2202.01649","author":"Viand Alexander","year":"2022","unstructured":"Alexander Viand, Patrick Jattke, Miro Haller, and Anwar Hithnawi. 2022. HECO: Automatic Code Optimizations for Efficient Fully Homomorphic Encryption. arxiv:2202.01649"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPEC.2012.6408660"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3696443.3708917"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/CSDE59766.2023.10487709"}],"event":{"name":"CGO '25: 23rd ACM\/IEEE International Symposium on Code Generation and Optimization","location":"Las Vegas NV USA","acronym":"CGO '25","sponsor":["SIGPLAN SIGPLAN Programming Languages","SIGMICRO SIGMICRO Microarchitecture","IEEE Computer Society IEEE Computer Society"]},"container-title":["Proceedings of the 23rd ACM\/IEEE International Symposium on Code Generation and Optimization"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696443.3708924","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:10:13Z","timestamp":1750295413000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696443.3708924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":53,"alternative-id":["10.1145\/3696443.3708924","10.1145\/3696443"],"URL":"https:\/\/doi.org\/10.1145\/3696443.3708924","relation":{},"subject":[],"published":{"date-parts":[[2025,3]]},"assertion":[{"value":"2025-03-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}