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GTC ON-DEMAND

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Abstract:
Conducting deep learning research and development requires a combination of cutting-edge hardware, elastic software frameworks, and a collaborative research community. We'll provide the scaffolding for participants to construct an enterprise-scale, GPU-enabled high performance computing solution for machine learning and data science by drawing on the experiences gained while IBM Research built its Cognitive Computing Cluster. We'll start by discussing how to build a secure, shared-resource computing cluster optimized for deep learning. Next, we'll cover how to provide deep learning frameworks supporting speech, vision, language, and text processing and their underlying primitives. Finally, we'll discuss how to build a best practice knowledge base to improve research quality and accelerate discovery.
Conducting deep learning research and development requires a combination of cutting-edge hardware, elastic software frameworks, and a collaborative research community. We'll provide the scaffolding for participants to construct an enterprise-scale, GPU-enabled high performance computing solution for machine learning and data science by drawing on the experiences gained while IBM Research built its Cognitive Computing Cluster. We'll start by discussing how to build a secure, shared-resource computing cluster optimized for deep learning. Next, we'll cover how to provide deep learning frameworks supporting speech, vision, language, and text processing and their underlying primitives. Finally, we'll discuss how to build a best practice knowledge base to improve research quality and accelerate discovery.  Back
 
Topics:
Data Center & Cloud Infrastructure, Artificial Intelligence and Deep Learning, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7350
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