BSTC-Reference-Cited by-同舟云学术

BSTC

Published:2019-11-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
language:
Short-container-title:

Author:

Li Ang¹,Geng Tong²,Wang Tianqi²,Herbordt Martin²,Song Shuaiwen Leon¹,Barker Kevin¹

Affiliation:

1. Pacific Northwest National Lab

2. Boston University

Funder

Laboratory Directed Research and Development

Pacific Northwest National Laboratory

Advanced Scientific Computing Research

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3295500.3356169

Reference80 articles.

1. Classification of the hadronic decays of the Z0 into b and c quark pairs using a neural network

2. A Dynamic Hash Table for the GPU

3. Efficiency of quantum vs. classical annealing in nonconvex learning problems

4. Pierre Baldi Kyle Cranmer Taylor Faucett Peter Sadowski and Daniel Whiteson. 2016. Parameterized machine learning for high-energy physics. arXiv preprint arXiv:1601.07913 (2016). Pierre Baldi Kyle Cranmer Taylor Faucett Peter Sadowski and Daniel Whiteson. 2016. Parameterized machine learning for high-energy physics. arXiv preprint arXiv:1601.07913 (2016).

5. Tal Ben-Nun and Torsten Hoefler. 2018. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis. arXiv preprint arXiv:1802.09941 (2018). Tal Ben-Nun and Torsten Hoefler. 2018. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis. arXiv preprint arXiv:1802.09941 (2018).

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