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UID:submissions.supercomputing.org_SC19_sess339_bof206@linklings.com
SUMMARY:Benchmarking Machine Learning Ecosystem on HPC Systems
DESCRIPTION:Birds of a Feather\n\nBenchmarking Machine Learning Ecosystem 
 on HPC Systems\n\nEmani, Malik, Balma, Farrell\n\nHigh-performance computi
 ng is seeing an upsurge in workloads that require data analysis. Machine l
 earning and Deep learning models are used in several science domains such 
 as cosmology, particle physics, biology with data in unprecedented scale f
 rom simulations. These applications include tasks such as image detection,
  segmentation, synthetic data generation and in-situ data analysis. Emergi
 ng HPC systems have diverse hardware including many-core, multi-core and h
 eterogeneous accelerators. It is critical to understand the performance of
  Machine learning/deep learning models on HPC systems at scale. Benchmarki
 ng will help to better understand the model-system interactions and help c
 o-design future HPC systems for ML workloads.\n\nTag: Tech Program Reg Pas
 s, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass, Benchmarks, H
 PC, Machine Learning\n\nRegistration Category: Tech Program Reg Pass, Exhi
 bits Reg Pass, Exhibits - Exhibit Hall Only Reg Pass, Benchmarks, HPC, Mac
 hine Learning
URL:https://sc19.supercomputing.org/presentation/?id=bof206&sess=sess339
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