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The Deep Learning on Supercomputers Workshop

The Deep Learning (DL) on Supercomputers workshop will be held with the SC’19 conference in Denver, CO, on Nov 17th, 2019. This third workshop in the Deep Learning on Supercomputers series provides a forum for practitioners working on any and all aspects of DL for scientific research in the High Performance Computing (HPC) context to present their latest research results. The general theme of this workshop series is the intersection of DL and HPC. Its scope encompasses application development in scientific scenarios using HPC platforms; DL methods applied to numerical simulation; fundamental algorithms, enhanced procedures, and software development methods to enable scalable training and inference; hardware changes with impact on future supercomputer design; and machine deployment, performance evaluation, and reproducibility practices for DL applications, with an emphasis on scientific usage.

Topics include but are not limited to:

As part of the reproducibility initiative, the workshop requires authors to provide information such as the algorithms, software releases, datasets, and hardware configurations used. For performance evaluation studies, we will encourage authors to use well-known benchmarks or applications with open accessible datasets: for example, MLPerf and ResNet-50 with the ImageNet-1K dataset.

For questions, please contact (

Import Dates (Tentative)

Paper Submission

Authors are invited to submit unpublished, original work with a minimum of 6 and a maximum of 8 pages (excluding references) in IEEE conference format and submitted using Linklings (login required). IEEE TCHPC conditionally agrees to publish accepted papers.

Organizing Committee

Previous Workshop

1st Deep Learning on Supercomputers Workshop in SC’18 in Dallas, USA

2nd Deep Learning for Science Workshop in ISC’19 in Frankfurt, Germany