In the published article, there was an error regarding the affiliation for author Anne-Sophie Berthold. Instead of having affiliation 25 (Cerebras Systems, Sunnyvale, CA, United States) they should have 14 (Institute of Nuclear and Particle Physics, Technische Universität Dresden, Dresden, Germany).
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Statements
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Summary
Keywords
machine learning for science, big data, particle physics, codesign, coprocessors, heterogeneous computing, fast machine learning
Citation
Deiana AM, Tran N, Agar J, Blott M, Di Guglielmo G, Duarte J, Harris P, Hauck S, Liu M, Neubauer MS, Ngadiuba J, Ogrenci-Memik S, Pierini M, Aarrestad T, Bähr S, Becker J, Berthold A-S, Bonventre RJ, Müller Bravo TE, Diefenthaler M, Dong Z, Fritzsche N, Gholami A, Govorkova E, Guo D, Hazelwood KJ, Herwig C, Khan B, Kim S, Klijnsma T, Liu Y, Lo KH, Nguyen T, Pezzullo G, Rasoulinezhad S, Rivera RA, Scholberg K, Selig J, Sen S, Strukov D, Tang W, Thais S, Unger KL, Vilalta R, von Krosigk B, Wang S and Warburton TK (2023) Corrigendum: Applications and techniques for fast machine learning in science. Front. Big Data 6:1301942. doi: 10.3389/fdata.2023.1301942
Received
25 September 2023
Accepted
26 September 2023
Published
16 October 2023
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
6 - 2023
Updates
Copyright
© 2023 Deiana, Tran, Agar, Blott, Di Guglielmo, Duarte, Harris, Hauck, Liu, Neubauer, Ngadiuba, Ogrenci-Memik, Pierini, Aarrestad, Bähr, Becker, Berthold, Bonventre, Müller Bravo, Diefenthaler, Dong, Fritzsche, Gholami, Govorkova, Guo, Hazelwood, Herwig, Khan, Kim, Klijnsma, Liu, Lo, Nguyen, Pezzullo, Rasoulinezhad, Rivera, Scholberg, Selig, Sen, Strukov, Tang, Thais, Unger, Vilalta, von Krosigk, Wang and Warburton.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Allison McCarn Deiana adeiana@smu.eduNhan Tran ntran@fnal.gov
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.