{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T13:47:25Z","timestamp":1782481645441,"version":"3.54.5"},"reference-count":57,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U24A20235, 62225205, and T2422007"],"award-info":[{"award-number":["U24A20235, 62225205, and T2422007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Archit. Code Optim."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>\n                    Existing tile size selection approaches are tightly coupled with compiler transformation pipelines, often leading to inaccurate modeling of cache behavior and limited effectiveness for non-rectangular tile shapes. This article presents\n                    <jats:sc>TileMind<\/jats:sc>\n                    , a decoupled analytical model that combines compile-time and runtime information for tile size selection in affine programs. It introduces a transformation-aware pre-tiling step that enables the decoupled selector to remain consistent with compiler transformations while extracting compile-time metadata. The extracted metadata is then combined with profiled runtime characteristics to construct a richer yet tractable feasible domain, within which a nonlinear objective for tile size selection is formulated. This objective is subsequently transformed into a binary product linearization problem, with its nonlinear constraints also linearized for efficient optimization. Finally, an intra-tile optimization aligns computation with data layout to enhance data reuse within tiles. Across two multi-core Intel CPUs,\n                    <jats:sc>TileMind<\/jats:sc>\n                    achieves 1.49\u00d7 (sequential) and 1.33\u00d7 (parallel) mean speedups on twenty PolyBench kernels, and 2.08\u20133.54\u00d7 speedups on three deep learning workloads over the state-of-the-art analytical model\n                    <jats:sc>Pluto-tss<\/jats:sc>\n                    . Compared with TVM\u2019s latest autotuner MetaSchedule,\n                    <jats:sc>TileMind<\/jats:sc>\n                    delivers 1.35\u20131.46\u00d7 mean speedups while reducing tuning overhead by 2\u20134 orders of magnitude. While demonstrating effectiveness on selecting tile sizes for non-rectangular tile shapes and compatibility with PPCG, Pluto, and TVM, we further provide proof-of-concept results on GPUs, illustrating the potential portability of\n                    <jats:sc>TileMind<\/jats:sc>\n                    across architectures.\n                  <\/jats:p>","DOI":"10.1145\/3806056","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:06:09Z","timestamp":1776078369000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Decoupled Analytical Model for Tile Size Selection in Affine Programs"],"prefix":"10.1145","volume":"23","author":[{"given":"Shihan","family":"Yuan","sequence":"first","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zuoyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanghui","family":"Song","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhui","family":"Peng","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuo","family":"Tang","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenli","family":"Li","sequence":"additional","affiliation":[{"name":"Computer Science, Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2303-9736","authenticated-orcid":false,"given":"Jie","family":"Zhao","sequence":"additional","affiliation":[{"name":"Hunan University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447818.3460369"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/SUPERC.1990.129995"},{"key":"e_1_3_3_4_2","unstructured":"Apache. 2025. TVM 0.22.0. Retrieved February 5 2026 from https:\/\/github.com\/apache\/tvm\/tree\/v0.22.0"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3650200.3656630"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.5555\/548834"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/263580.263662"},{"key":"e_1_3_3_8_2","unstructured":"Uday Bondhugula. 2025. Pluto 0.12.0. Retrieved February 5 2026 from https:\/\/github.com\/bondhugula\/pluto\/tree\/0.12.0"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2016.2615094"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/1375581.1375595"},{"key":"e_1_3_3_11_2","series-title":"OSDI\u201918","first-page":"579","volume-title":"Proceedings of the 13th USENIX Conference on Operating Systems Design and Implementation","author":"Chen Tianqi","year":"2018","unstructured":"Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy. 2018. TVM: An automated end-to-end optimizing compiler for deep learning. In Proceedings of the 13th USENIX Conference on Operating Systems Design and Implementation (OSDI\u201918). USENIX Association, USA, 579\u2013594."},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8191(00)00087-9"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/207110.207162"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","unstructured":"Jacob Devlin Ming-Wei Chang Kenton Lee and Kristina Toutanova. 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Volume 1 (Long and Short Papers) 1 (2019) 4171\u20134186. DOI:10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF01379404"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3559009.3569678"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/1356052.1356053"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/2544137.2544160"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0129626412500107"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/2743016"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404846"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/CGO57630.2024.10444795"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/1250734.1250761"},{"key":"e_1_3_3_24_2","volume-title":"Advances in Neural Information Processing Systems","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. ImageNet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems. F. Pereira, C. J. Burges, L. Bottou, and K. Q. Weinberger (Eds.), Vol. 25, Curran Associates, Inc. Retrieved from https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2012\/file\/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/106972.106981"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3445814.3446759"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3293883.3295734"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3632894"},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-021-03835-z"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/2925987"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/2541228.2555292"},{"key":"e_1_3_3_32_2","first-page":"25","article-title":"Pulp: A Linear Programming Toolkit for Python","volume":"65","author":"Mitchell Stuart","year":"2011","unstructured":"Stuart Mitchell, Michael OSullivan, and Iain Dunning. 2011. Pulp: A Linear Programming Toolkit for Python. The University of Auckland, Auckland, New Zealand 65 (2011), 25.","journal-title":"The University of Auckland, Auckland, New Zealand"},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.1109\/PACT52795.2021.00011"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/2897824.2925952"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/2694344.2694364"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447818.3462213"},{"key":"e_1_3_3_37_2","first-page":"90","volume-title":"Proceedings of the 2006 GCC Developers Summit","volume":"6","author":"Pop Sebastian","year":"2006","unstructured":"Sebastian Pop, Albert Cohen, C\u00e9dric Bastoul, Sylvain Girbal, Georges-Andr\u00e9 Silber, and Nicolas Vasilache. 2006. GRAPHITE: Polyhedral analyses and optimizations for GCC. In Proceedings of the 2006 GCC Developers Summit 6 (2006), 90\u201391."},{"key":"e_1_3_3_38_2","unstructured":"Louis-No\u00ebl Pouchet and Tomofumi Yuki. 2016. PolyBench\/C 4.2. Retrieved February 5 2026 from https:\/\/sourceforge.net\/projects\/polybench"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/2491956.2462176"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1109\/SC.2004.3"},{"key":"e_1_3_3_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/SC.2008.5213293"},{"key":"e_1_3_3_42_2","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2593"},{"key":"e_1_3_3_43_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-28652-0_6"},{"key":"e_1_3_3_44_2","doi-asserted-by":"publisher","DOI":"10.1145\/3168823"},{"key":"e_1_3_3_45_2","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969173"},{"key":"e_1_3_3_46_2","doi-asserted-by":"publisher","DOI":"10.1145\/3674735"},{"key":"e_1_3_3_47_2","doi-asserted-by":"publisher","DOI":"10.1145\/3570641"},{"key":"e_1_3_3_48_2","unstructured":"Hrishikesh Vaidya Akilesh Badrinaaraayanan Abhishek A. Patwardhan and Ramakrishna Upadrasta. 2017. PolyBench\/polyNN. Retrieved February 5 2026 from https:\/\/github.com\/IITH-Compilers\/PolyBench-NN"},{"key":"e_1_3_3_49_2","doi-asserted-by":"publisher","DOI":"10.1145\/3355606"},{"key":"e_1_3_3_50_2","unstructured":"Sven Verdoolaege. 2024. PPCG 0.09.2. Retrieved February 5 2026 from https:\/\/repo.or.cz\/ppcg.git\/tag\/30b6868299930df35fac8227b58f77cd292a89a9"},{"key":"e_1_3_3_51_2","doi-asserted-by":"publisher","DOI":"10.1145\/2400682.2400713"},{"key":"e_1_3_3_52_2","doi-asserted-by":"publisher","DOI":"10.1145\/3627535.3638484"},{"key":"e_1_3_3_53_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2022.102799"},{"key":"e_1_3_3_54_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2004.840444"},{"key":"e_1_3_3_55_2","doi-asserted-by":"publisher","DOI":"10.1145\/1772954.1772982"},{"key":"e_1_3_3_56_2","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO50266.2020.00044"},{"key":"e_1_3_3_57_2","doi-asserted-by":"publisher","DOI":"10.1145\/3178372.3179509"},{"key":"e_1_3_3_58_2","series-title":"OSDI\u201920","volume-title":"Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation","author":"Zheng Lianmin","year":"2020","unstructured":"Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, and Ion Stoica. 2020. Ansor: Generating high-performance tensor programs for deep learning. In Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (OSDI\u201920). USENIX Association, USA, Article 49, 17 pages."}],"container-title":["ACM Transactions on Architecture and Code Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3806056","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:57:02Z","timestamp":1782478622000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3806056"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,26]]},"references-count":57,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,6,30]]}},"alternative-id":["10.1145\/3806056"],"URL":"https:\/\/doi.org\/10.1145\/3806056","relation":{},"ISSN":["1544-3566","1544-3973"],"issn-type":[{"value":"1544-3566","type":"print"},{"value":"1544-3973","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,26]]},"assertion":[{"value":"2025-12-11","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-23","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-26","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}