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GTC ON-DEMAND

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Abstract:

AI methods and tools are starting to be applied to HPC applications by a growing number of brave researchers in diverse scientific fields. This talk will describe an emergent workflow that uses traditional HPC numeric simulations to generate the labeled data sets required 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.

AI methods and tools are starting to be applied to HPC applications by a growing number of brave researchers in diverse scientific fields. This talk will describe an emergent workflow that uses traditional HPC numeric simulations to generate the labeled data sets required 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.

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Topics:
HPC and AI
Type:
Talk
Event:
Supercomputing
Year:
2018
Session ID:
SC1814
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Abstract:

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. Now, AI methods and tools are starting to be applied to HPC applications to great effect. This talk will describe an emergent workflow that uses traditional HPC numeric simulations to generate the labeled data sets required 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.

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. Now, AI methods and tools are starting to be applied to HPC applications to great effect. This talk will describe an emergent workflow that uses traditional HPC numeric simulations to generate the labeled data sets required 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.

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Topics:
HPC and Supercomputing
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8175
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Abstract:
HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by letting researchers analyze massive amounts of data faster and more effectively. Its a transformational new tool for gaining insights where simulation alone cannot fully predict the real world.
HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by letting researchers analyze massive amounts of data faster and more effectively. Its a transformational new tool for gaining insights where simulation alone cannot fully predict the real world.  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
SIGGRAPH
Year:
2017
Session ID:
SC1721
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Abstract:

The emergence of heterogeneous computing has demonstrated that the highest performance and efficiency can be achieved in a general way by tightly coupling compute engines optimized for latency-sensitive and throughput-oriented operations. This talk will explore heterogeneous node design and architecture and how NVLink, a new scalable node integration channel, enables uncompromising performance on the most demanding applications, using the next-generation DoE CORAL Summit and Sierra supercomputer systems as a case in point.

The emergence of heterogeneous computing has demonstrated that the highest performance and efficiency can be achieved in a general way by tightly coupling compute engines optimized for latency-sensitive and throughput-oriented operations. This talk will explore heterogeneous node design and architecture and how NVLink, a new scalable node integration channel, enables uncompromising performance on the most demanding applications, using the next-generation DoE CORAL Summit and Sierra supercomputer systems as a case in point.

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Topics:
HPC and Supercomputing, Data Center & Cloud Infrastructure
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5649
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