GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments

GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments

Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the data volumes of such experiments are rapidly increasing. Th...

Full description

Bibliographic Details
Main Authors: Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey Krupa, Kevin Pedro, Nhan Tran
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Big Data
Subjects:
machine learning
heterogeneous (CPU+GPU) computing
GPU (graphics processing unit)
particle physics
cloud computing (SaaS)
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2020.604083/full

Internet

https://www.frontiersin.org/articles/10.3389/fdata.2020.604083/full

Similar Items