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GTC ON-DEMAND

Data Center & Cloud Infrastructure
Presentation
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Exploring GPU Inference in the Datacenter
Abstract:
New algorithms leverage the algebraic strengths of GPUs far beyond rendering visuals. They unlock opportunities for data analysis leveraging computer vision and artificial neural networks. Earlier this year we set out to investigate the deployment of power-efficient GPUs in commodity hardware. We did not focus on supercomputers, but instead exercised GPUs within a homogeneous set of compute nodes like those used to scale Apache Hadoop or Apache Spark clusters. Our work focused on inference deploying models and GPU acceleration for analysis tasks such as feature extraction, identification, and classification not on training or building models, tasks likely better suited to HPC-class machines. Our experiments investigated applications that aren't feasible at scale on existing CPUs, such as malware detection and object detection in images. We'll cover inference on Tesla P4 GPUs in scale-out architectures, leveraging nvidia-docker, Caffe, Torch, and TensorRT.
 
Topics:
Data Center & Cloud Infrastructure, Artificial Intelligence and Deep Learning, Accelerated Data Science
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7190
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