Accelerated Machine Learning as a Service for Particle Physics Computing

Duarte, Javier; Holzman, Burt; Jindariani, Sergo; Klijnsma, Thomas; Kreis, Benjamin; Liu, Mia; Pedro, Kevin; Tran, Nhan; Tsaris, Aristeidis; Harris, Phil; Rankin, Dylan; Loncar, Vladimir; Ngadiuba, Jennifer; Pierini, Maurizio; Khan, Suffian; Lee, Brian; Perez, Brandon; Way, Ted W.; Versteeg, Colin; Hauck, Scott; Hsu, Shih-Chieh; Trahms, Matthew; Werran, Dustin; Wu, Zhenbin

doi:10.2172/1592124

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Accelerated Machine Learning as a Service for Particle Physics Computing

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Abstract

Accelerated Machine Learning as a Service for Particle Physics Computing: • Amount and complexity of high-energy physics data increases dramatically from 2025 onward • Traditional algorithms will require too much CPU time • Machine learning can solve combinatorially-scaling problems in constant time, but must be fast enough

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Duarte, Javier, Holzman, Burt, Jindariani, Sergo, Klijnsma, Thomas, Kreis, Benjamin, Liu, Mia, Pedro, Kevin, Tran, Nhan, Tsaris, Aristeidis, Harris, Phil, Rankin, Dylan, Loncar, Vladimir, Ngadiuba, Jennifer, Pierini, Maurizio, Khan, Suffian, Lee, Brian, Perez, Brandon, Way, Ted W., Versteeg, Colin, Hauck, Scott, Hsu, Shih-Chieh, Trahms, Matthew, Werran, Dustin, Wu, Zhenbin. 2019-01-01. Accelerated Machine Learning as a Service for Particle Physics Computing. https://doi.org/10.2172/1592124

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