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GTC ON-DEMAND

Data Center & Cloud Infrastructure
Presentation
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Architecting a Complete Data Infrastructure for AI and Deep Learning (Presented by NetApp)
Abstract:
Enterprises are eager to take advantage of artificial intelligence technologies such as deep learning to introduce new services and enhance insights from company data. As data science teams move past proof of concept and begin to operationalize deep learning, it becomes necessary to focus on the creation of a complete data architecture that eliminates bottlenecks to facilitate faster model iteration. Designing a data architecture involves thinking holistically about the deep learning pipeline, from data ingest and edge analytics, to data prep and training in the core data center, to archiving in the cloud. It is necessary to understand performance requirements and data services needed, but one should also consider future extensibility and supportability as deep learning hardware and cloud approaches evolve over time. This session will examine all the factors involved in the architecture of a deep learning pipeline, focusing in on data management and the hybrid cloud. Careful infrastructure planning can smooth the flow of data through your deep learning pipeline, lead to faster time to deployment, and thus maximum competitive differentiation.
 
Topics:
Data Center & Cloud Infrastructure, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8974
Streaming:
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