{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:09:06Z","timestamp":1775779746697,"version":"3.50.1"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"CRISP"},{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SRC Global Research Collaboration"},{"name":"DARPA HyDDENN"},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1911095"],"award-info":[{"award-number":["1911095"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2003279"],"award-info":[{"award-number":["2003279"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2100237"],"award-info":[{"award-number":["2100237"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008982","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2120019"],"award-info":[{"award-number":["2120019"]}],"id":[{"id":"10.13039\/501100008982","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2018R1A5A1060031"],"award-info":[{"award-number":["NRF-2018R1A5A1060031"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2022,11,1]]},"DOI":"10.1109\/tc.2022.3179226","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T19:38:52Z","timestamp":1654025932000},"page":"2753-2765","source":"Crossref","is-referenced-by-count":26,"title":["OpenHD: A GPU-Powered Framework for Hyperdimensional Computing"],"prefix":"10.1109","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1048-1285","authenticated-orcid":false,"given":"Jaeyoung","family":"Kang","sequence":"first","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3655-0501","authenticated-orcid":false,"given":"Behnam","family":"Khaleghi","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]},{"given":"Tajana","family":"Rosing","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA, USA"}]},{"given":"Yeseong","family":"Kim","sequence":"additional","affiliation":[{"name":"Daegu Gyeongbuk Institute of Science and Technology, Daegu, South Korea"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Sparse Distributed Memory","author":"Kanerva","year":"1988"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.23919\/DATE48585.2020.9116397"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2934583.2934624"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aaw6736"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICRC.2017.8123650"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2014.2320573"},{"key":"ref7","first-page":"384","article-title":"HyperRec: Efficient recommender systems with hyperdimensional computing","volume-title":"Proc. 26th Asia South Pacific Des. Automat. Conf.","author":"Guo"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC44109.2020.9175328"},{"key":"ref9","article-title":"The kanerva machine: A generative distributed memory","author":"Wu","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-020-0410-3"},{"key":"ref11","article-title":"Properties of sparse distributed representations and their application to hierarchical temporal memory","author":"Ahmad","year":"2015"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JETCAS.2019.2935464"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA.2017.28"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2019.8714821"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240811"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IEDM.2016.7838428"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO50266.2020.00039"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MASCOTS53633.2021.9614302"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2814400"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ASP-DAC52403.2022.9712549"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-009-9009-8"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2017.2705051"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3277593.3277617"},{"key":"ref24","article-title":"Hyperdimensional computing for text classification","volume-title":"Proc. Des., Autom. Test Eur. Conf. Exhib. exhibition (DATE), Univ. Booth","author":"Najafabadi"},{"key":"ref25","article-title":"Language recognition using random indexing","author":"Joshi","year":"2014"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3289602.3293913"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BIOCAS.2019.8918974"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2019.8715147"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.parco.2011.09.001"},{"key":"ref30","article-title":"Astor","author":"Peksag","year":"2020"},{"key":"ref31","first-page":"1","article-title":"BRIC: Locality-based encoding for energy-efficient brain-inspired hyperdimensional computing","volume-title":"Proc. 56th Annu. Des. Automat. Conf.","author":"Imani"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330648"},{"key":"ref33","first-page":"1027","article-title":"K-means : The advantages of careful seeding","volume-title":"Proc. 18th Annu. ACM-SIAM Symp. Discrete Algorithms","author":"Arthur"},{"key":"ref34","article-title":"UCI machine learning repository","author":"Dua","year":"2017"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2012.13"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.3390\/data5010013"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ISLPED.2019.8824908"},{"key":"ref38","article-title":"TensorRT","year":"2020"},{"key":"ref39","first-page":"579","article-title":"TVM: An automated end-to-end optimizing compiler for deep learning","volume-title":"Proc. 13th USENIX Conf. Oper. Syst. Des. Implementation","author":"Chen"},{"key":"ref40","article-title":"CuPy: A numpy-compatible library for NVIDIA GPU calculations","volume-title":"Proc. 31st Conf. Neural Inf. Process. Syst.","volume":"151","author":"Nishino"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-11970-5_14"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2833157.2833162"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2014.07.003"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/P3HPC49587.2019.00012"},{"key":"ref45","first-page":"1","article-title":"SynergicLearning: Neural network-based feature extraction for highly-accurate hyperdimensional learning","volume-title":"Proc. IEEE\/ACM Int. Conf. Comput. Aided Des.","author":"Nazemi"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/12\/9913765\/9785847-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/12\/9913765\/09785847.pdf?arnumber=9785847","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T03:24:01Z","timestamp":1706757841000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9785847\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,1]]},"references-count":45,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tc.2022.3179226","relation":{},"ISSN":["0018-9340","1557-9956","2326-3814"],"issn-type":[{"value":"0018-9340","type":"print"},{"value":"1557-9956","type":"electronic"},{"value":"2326-3814","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,1]]}}}