Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Matthew Trahms"'
Autor:
Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Scott Hauck, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark Neubauer, Isobel Ojalvo, Savannah Thais, Matthew Trahms
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase o
Externí odkaz:
https://doaj.org/article/3539277e3915499d865f3af74e494f03
Autor:
Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Scott Hauck, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark Neubauer, Isobel Ojalvo, Savannah Thais, Matthew Trahms
Publikováno v:
Frontiers in big data. 5
The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::decd6ad1d14302844f56ead29a1ed530
https://pubmed.ncbi.nlm.nih.gov/35402906
https://pubmed.ncbi.nlm.nih.gov/35402906
Autor:
Burt Holzman, Shih-Chieh Hsu, Kelvin Lin, Thomas Klijnsma, Dylan Rankin, Yu Lou, Kevin Pedro, Philip Harris, Javier Duarte, Matthew Trahms, Scott Hauck, Nhan Tran, Maria Acosta Flechas, Jeffrey Krupa, Mia Liu, Ta-Wei Ho
Publikováno v:
H2RC@SC
DOE / OSTI
DOE / OSTI
Computing needs for high energy physics are already intensive and are expected to increase drastically in the coming years. In this context, heterogeneous computing, specifically as-a-service computing, has the potential for significant gains over tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86cdd16f91ef5bf97dab2923afd43eb2
http://arxiv.org/abs/2010.08556
http://arxiv.org/abs/2010.08556
Autor:
Burt Holzman, Colin Versteeg, A. Tsaris, Suffian Khan, Brandon Perez, Brian Lee, Benjamin Kreis, Maurizio Pierini, Sergo Jindariani, Ted W. Way, Javier Duarte, Thomas Klijnsma, Nhan Tran, Vladimir Loncar, Phil Harris, Mia Liu, Zhenbin Wu, Scott Hauck, Matthew Trahms, Dylan Rankin, Shih-Chieh Hsu, Kevin Pedro, Dustin Werran, Jennifer Ngadiuba
Large-scale particle physics experiments face challenging demands for high- throughput computing resources both now and in the future. New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dfe743f81b901c58a6ae8b1991aa0f5
Autor:
Nhan Tran, Ted W. Way, Shih-Chieh Hsu, Philip Harris, Benjamin Kreis, Zhenbin Wu, Scott Hauck, Brandon Perez, Jennifer Ngadiuba, Suffian Khan, Burt Holzman, Sergo Jindariani, Mia Liu, Dylan Rankin, Maurizio Pierini, A. Tsaris, Dustin Werran, Matthew Trahms, Javier Duarte, Vladimir Loncar, Kevin Pedro, Colin Versteeg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f87f50c6a296e440685908a41bb19c8
https://doi.org/10.2172/1570210
https://doi.org/10.2172/1570210
Autor:
Jeffrey Krupa, Maria Acosta Flechas, Kelvin Lin, Jack Dinsmore, Javier Duarte, Scott Hauck, Nhan Tran, Burt Holzman, Natchanon Suaysom, Mia Liu, Thomas Klijnsma, Kevin Pedro, Philip Harris, Dylan Rankin, Matthew Trahms, Shih-Chieh Hsu
Publikováno v:
Machine Learning: Science and Technology. 2:035005
In the next decade, the demands for computing in large scientific experiments are expected to grow tremendously. During the same time period, CPU performance increases will be limited. At the CERN Large Hadron Collider (LHC), these two issues will co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83450aa7b31930901db6da559af4eacb
https://doi.org/10.1088/2632-2153/abec21
https://doi.org/10.1088/2632-2153/abec21
Autor:
Brandon Perez, Brian Lee, Ted W. Way, Kevin Pedro, Dylan Rankin, Maurizio Pierini, Zhenbin Wu, A. Tsaris, Javier Duarte, Colin Versteeg, Scott Hauck, Burt Holzman, Philip Harris, Mia Liu, Suffian Khan, Benjamin Kreis, Nhan Tran, Vladimir Loncar, Matthew Trahms, Jennifer Ngadiuba, Shih-Chieh Hsu, Sergo Jindariani, Dustin Werran
Publikováno v:
Springer International Publishing
Computing and Software for Big Science
Computing and Software for Big Science
New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains. The growing applications of machine learning algorithms i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de949dd2acd143aee9ec86e0f7799f30