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GTC ON-DEMAND

Computational Biology & Chemistry
Presentation
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Buildling Exascale Deep Learning Tools to Help Understand Cancer Biology at the Molecular Scale
Abstract:

Understanding the biology of cancer at the molecular scale is a critical challenge for the RAS oncogene family of cancers. We are developing an adaptive molecular dynamics simulation framework that uses multi-scale models to achieve simulation time scales that allow biologically interesting behaviors to emerge. We'll develop new deep learning techniques that can help identify phase transitions, the formation of complex structures, and the detection of interesting events between the RAS protein and cell membrane. This molecular dynamics simulation data will drive the need for new techniques in both model and data parallelism within deep learning toolkits, and require the capabilities of next-generation supercomputers such as SIERRA and Summit at LLNL and ORNL, respectively.

 
Topics:
Computational Biology & Chemistry, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7792
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