HPC + Ai: Machine Learning Models in Scientific Computing.
HPC + Ai: Machine Learning Models in Scientific Computing [link]Paper  abstract   bibtex   
In this video from the 2019 Stanford HPC Conference, Steve Oberlin from NVIDIA presents: HPC + Ai: Machine Learning Models in Scientific Computing. "Most AI researchers and industry pioneers agree that the wide availability and low cost of highly-efficient and powerful GPUs and accelerated computing parallel programming tools (originally developed to benefit HPC applications) catalyzed the modern revolution in AI/deep learning. Clearly, AI has benefited greatly from HPC. Now, AI methods and tools are starting to be applied to HPC applications to great effect. This talk will describe an emerging workflow that uses traditional numeric simulation codes to generate synthetic data sets to train machine learning algorithms, then employs the resulting AI models to predict the computed results, often with dramatic gains in efficiency, performance, and even accuracy. Some compelling success stories will be shared, and the implications of this new HPC + AI workflow on HPC applications and system architecture in a post-Moore’s Law world considered." Watch the video: https://youtu.be/SV3cnWf39kc Learn more: https://nvidia.com and http://hpcadvisorycouncil.com/events/... Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
@misc{noauthor_hpc_nodate,
	title = {{HPC} + {Ai}: {Machine} {Learning} {Models} in {Scientific} {Computing}},
	shorttitle = {{HPC} + {Ai}},
	url = {https://www.youtube.com/watch?time_continue=1&v=SV3cnWf39kc&feature=emb_title},
	abstract = {In this video from the 2019 Stanford HPC Conference, Steve Oberlin from NVIDIA presents: HPC + Ai: Machine Learning Models in Scientific Computing.

"Most AI researchers and industry pioneers agree that the wide availability and low cost of highly-efficient and powerful GPUs and accelerated computing parallel programming tools (originally developed to benefit HPC applications) catalyzed the modern revolution in AI/deep learning.  Clearly, AI has benefited greatly from HPC.  Now, AI methods and tools are starting to be applied to HPC applications to great effect. This talk will describe an emerging workflow that uses traditional numeric simulation codes to generate synthetic data sets to train machine learning algorithms, then employs the resulting AI models to predict the computed results, often with dramatic gains in efficiency, performance, and even accuracy. Some compelling success stories will be shared, and the implications of this new HPC + AI workflow on HPC applications and system architecture in a post-Moore’s Law world considered."

Watch the video: https://youtu.be/SV3cnWf39kc

Learn more: https://nvidia.com
and
http://hpcadvisorycouncil.com/events/...

Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter},
	urldate = {2019-11-19}
}

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