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GTC ON-DEMAND

Artificial Intelligence and Deep Learning
Presentation
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Optimizing Efficiency of Deep Learning Workloads through GPU Virtualization
Abstract:
Cognitive applications are reshaping the IT landscape with entire data centers designed and built solely for that purpose. Though computationally challenging, deep learning networks have become a critical building block to boost accuracy of cognitive offerings like Watson. We'll present a detailed performance study of deep learning workloads and how sharing accelerator resources can improve throughput by a factor of three, effectively turning a four GPU commodity cloud system into a high-end, 12-GPU supercomputer. Using Watson workloads from three major areas that incorporate deep learning technology (language classification, visual recognition, and speech recognition), we document effectiveness and scalability of this approach.
 
Topics:
Artificial Intelligence and Deep Learning, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7320
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