Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Trahms, Matthew"'
Autor:
Pappalardo, Alessandro, Umuroglu, Yaman, Blott, Michaela, Mitrevski, Jovan, Hawks, Ben, Tran, Nhan, Loncar, Vladimir, Summers, Sioni, Borras, Hendrik, Muhizi, Jules, Trahms, Matthew, Hsu, Shih-Chieh, Hauck, Scott, Duarte, Javier
We present extensions to the Open Neural Network Exchange (ONNX) intermediate representation format to represent arbitrary-precision quantized neural networks. We first introduce support for low precision quantization in existing ONNX-based quantizat
Externí odkaz:
http://arxiv.org/abs/2206.07527
Autor:
Elabd, Abdelrahman, Razavimaleki, Vesal, Huang, Shi-Yu, Duarte, Javier, Atkinson, Markus, DeZoort, Gage, Elmer, Peter, Hauck, Scott, Hu, Jin-Xuan, Hsu, Shih-Chieh, Lai, Bo-Cheng, Neubauer, Mark, Ojalvo, Isobel, Thais, Savannah, Trahms, Matthew
Publikováno v:
Front. Big Data 5 (2022) 828666
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:
http://arxiv.org/abs/2112.02048
Autor:
Rankin, Dylan Sheldon, Krupa, Jeffrey, Harris, Philip, Flechas, Maria Acosta, Holzman, Burt, Klijnsma, Thomas, Pedro, Kevin, Tran, Nhan, Hauck, Scott, Hsu, Shih-Chieh, Trahms, Matthew, Lin, Kelvin, Lou, Yu, Ho, Ta-Wei, Duarte, Javier, Liu, Mia
Publikováno v:
2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC), 2020, pp. 38-47
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:
http://arxiv.org/abs/2010.08556
Autor:
Duarte, Javier, Harris, Philip, Hauck, Scott, Holzman, Burt, Hsu, Shih-Chieh, Jindariani, Sergo, Khan, Suffian, Kreis, Benjamin, Lee, Brian, Liu, Mia, Lončar, Vladimir, Ngadiuba, Jennifer, Pedro, Kevin, Perez, Brandon, Pierini, Maurizio, Rankin, Dylan, Tran, Nhan, Trahms, Matthew, Tsaris, Aristeidis, Versteeg, Colin, Way, Ted W., Werran, Dustin, Wu, Zhenbin
Publikováno v:
Comput Softw Big Sci (2019) 3: 13
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:
http://arxiv.org/abs/1904.08986
Autor:
Elabd, Abdelrahman, Duarte, Javier Mauricio, Lai, Bo-Cheng, DeZoort, Gage, Ojalvo, Isobel, Neubauer, Mark, Atkinson, Markus Julian, Trahms, Matthew, Elmer, Peter, Thais, Savannah Jennifer, Hauck, Scott, Huang, Shi-Yu, Hsu, Shih-Chieh, Razavimaleki, Vesal
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___::9192d78ec73389d85fafdd1f4196cef1
Autor:
Trahms, Matthew Karl
The Large Hadron Collider produces a large amount of data while operating, approximately one petabyte of data per second. The collider is currently undergoing an upgrade to collide more particles and produce even more data. In order to handle this la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________65::e1ef10f1011a34a09e2b10430d32e44f
http://cds.cern.ch/record/2804953
http://cds.cern.ch/record/2804953
Autor:
Elabd A; Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, United States., Razavimaleki V; Department of Physics, University of California, San Diego, La Jolla, CA, United States., Huang SY; Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan., Duarte J; Department of Physics, University of California, San Diego, La Jolla, CA, United States., Atkinson M; Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States., DeZoort G; Department of Physics, Princeton University, Princeton, NJ, United States., Elmer P; Department of Physics, Princeton University, Princeton, NJ, United States., Hauck S; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States., Hu JX; Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan., Hsu SC; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.; Department of Physics, University of Washington, Seattle, WA, United States., Lai BC; Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan., Neubauer M; Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States., Ojalvo I; Department of Physics, Princeton University, Princeton, NJ, United States., Thais S; Department of Physics, Princeton University, Princeton, NJ, United States., Trahms M; Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States.
Publikováno v:
Frontiers in big data [Front Big Data] 2022 Mar 23; Vol. 5, pp. 828666. Date of Electronic Publication: 2022 Mar 23 (Print Publication: 2022).
