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4th DLS@SC 2020: Atlanta, GA, USA
- Fourth IEEE/ACM Workshop on Deep Learning on Supercomputers, DLS@SC 2020, Atlanta, GA, USA, November 11, 2020. IEEE 2020, ISBN 978-1-6654-2245-1
- Shogo Murai, Hiroaki Mikami, Masanori Koyama, Shuji Suzuki, Takuya Akiba:
Online-Codistillation Meets LARS, Going beyond the Limit of Data Parallelism in Deep Learning. 1-9 - Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams:
Time-Based Roofline for Deep Learning Performance Analysis. 10-19 - Bita Hasheminezhad, Shahrzad Shirzad, Nanmiao Wu, Patrick Diehl, Hannes Schulz, Hartmut Kaiser:
Towards a Scalable and Distributed Infrastructure for Deep Learning Applications. 20-30 - Matthijs Jansen, Valeriu Codreanu, Ana Lucia Varbanescu:
DDLBench: Towards a Scalable Benchmarking Infrastructure for Distributed Deep Learning. 31-39 - Alberto Acevedo, Michael Curry, Shantanu H. Joshi, Brett Leroux, Nicholas Malaya:
Vandermonde Wave Function Ansatz for Improved Variational Monte Carlo. 40-47 - Hamsa Shwetha Venkataram, Chris A. Mattmann, J. Scott Penberthy:
TopiQAL: Topic-aware Question Answering using Scalable Domain-specific Supercomputers. 48-55 - Maxwell X. Cai, Jeroen Bédorf, Vikram A. Saletore, Valeriu Codreanu, Damian Podareanu, Adel Chaibi, Penny X. Qian:
DeepGalaxy: Deducing the Properties of Galaxy Mergers from Images Using Deep Neural Networks. 56-62
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