{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T07:11:14Z","timestamp":1782544274414,"version":"3.54.5"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T00:00:00Z","timestamp":1750550400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T00:00:00Z","timestamp":1750550400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,22]]},"DOI":"10.1109\/dac63849.2025.11132525","type":"proceedings-article","created":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T17:35:41Z","timestamp":1757957741000},"page":"1-7","source":"Crossref","is-referenced-by-count":1,"title":["High-Performance Computing Architecture Exploration with Stage-Enhanced Bayesian Optimization"],"prefix":"10.1109","author":[{"given":"Vincent","family":"Fu","sequence":"first","affiliation":[{"name":"Universit&#x00E9; Paris-Saclay, CEA, List,Palaiseau,France,F-91120"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Benazouz","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; Paris-Saclay, CEA, List,Palaiseau,France,F-91120"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lilia","family":"Zaourar","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; Paris-Saclay, CEA, List,Palaiseau,France,F-91120"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alix","family":"Munier-Kordon","sequence":"additional","affiliation":[{"name":"Sorbonne Universit&#x00E9;, CNRS, LIP6,Paris,France,F-75005"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD51958.2021.9643455"},{"key":"ref2","article-title":"QEMU, a fast and portable dynamic translator","volume-title":"Proceedings of the annual conference on USENIX Annual Technical Conference (USENIX ATC)","author":"Bellard"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2010.2049053"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10288-011-0165-9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2024716.2024718"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.11.051"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3300189.3300192"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.mejo.2016.04.006"},{"key":"ref9","article-title":"State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning","author":"Das","year":"2022","journal-title":"arXiv preprint"},{"key":"ref10","article-title":"Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization","volume-title":"Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS)","author":"Daulton"},{"key":"ref11","article-title":"Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement","volume-title":"Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS)","author":"Daulton"},{"key":"ref12","article-title":"Multi-objective Bayesian optimization over high-dimensional search spaces","volume-title":"Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI)","author":"Daulton"},{"key":"ref13","article-title":"Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings","volume-title":"Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS)","author":"Deshwal"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/77626.79170"},{"key":"ref15","article-title":"Framework and benchmarks for combinatorial and mixed-variable bayesian optimization","volume-title":"Proceedings of the 37th International Conference on Neural Information Processing Systems Datasets and Benchmarks Track","author":"Dreczkowski"},{"key":"ref16","article-title":"Scalable Global Optimization via Local Bayesian Optimization","volume-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems (NeurIPS)","author":"Eriksson"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2011.01.004"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1287\/educ.2018.0188"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2001.968593"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.23919\/DATE54114.2022.9774632"},{"key":"ref21","doi-asserted-by":"crossref","DOI":"10.1145\/1669112.1669172","article-title":"McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures","volume-title":"Proceedings of the 42nd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO)","author":"Li"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA47549.2020.00018"},{"key":"ref23","article-title":"Memory bandwidth and machine balance in high performance computers","author":"McCalpin","year":"1995","journal-title":"IEEE Technical Committee on Computer Architecture Newsletter"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2007.33"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MASCOTS.2019.00053"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/774789.774804"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-017-7267-9_7"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/3206.001.0001"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2009.2035579"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"ref31","article-title":"Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the BlackBox Optimization Challenge 2020","volume-title":"Proceedings of the NeurIPS 2020 Competition and Demonstration Track","author":"Turner"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2016.2547387"},{"key":"ref33","article-title":"Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces","volume-title":"Proceedings of the 38th International Conference on Machine Learning (ICML)","author":"Wan"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2006.75"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/4235.585893"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1080\/10867651.1997.10487471"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143980"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD51958.2021.9643508"}],"event":{"name":"2025 62nd ACM\/IEEE Design Automation Conference (DAC)","location":"San Francisco, CA, USA","start":{"date-parts":[[2025,6,22]]},"end":{"date-parts":[[2025,6,25]]}},"container-title":["2025 62nd ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11132383\/11132091\/11132525.pdf?arnumber=11132525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T05:30:29Z","timestamp":1758000629000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11132525\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,22]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/dac63849.2025.11132525","relation":{},"subject":[],"published":{"date-parts":[[2025,6,22]]}}}