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Abstract:
We describes concept of Digital Twin with respect to the Railway Network. Railroad customers across the world manage thousands of miles of Track infrastructure that consists of the Rails, Ballast, Ties, Bridges, Tunnels, Wayside equipment, etc. This talk demonstrates a new approach to Track infrastructure monitoring that GE is piloting for customers using the concept of Digital Twin for network. Using an offline GPU infrastructure Deep Learning models are created and trained on large volumes of video data to learn the state of healthy Track and predict anomalies. During the talk, real customer use-case videos will be shown that demonstrate Analytics on videos from Locomotive-mounted cameras with Deep Learning models to calculate health index and display on a map for driving Maintenance decisions.
We describes concept of Digital Twin with respect to the Railway Network. Railroad customers across the world manage thousands of miles of Track infrastructure that consists of the Rails, Ballast, Ties, Bridges, Tunnels, Wayside equipment, etc. This talk demonstrates a new approach to Track infrastructure monitoring that GE is piloting for customers using the concept of Digital Twin for network. Using an offline GPU infrastructure Deep Learning models are created and trained on large volumes of video data to learn the state of healthy Track and predict anomalies. During the talk, real customer use-case videos will be shown that demonstrate Analytics on videos from Locomotive-mounted cameras with Deep Learning models to calculate health index and display on a map for driving Maintenance decisions.  Back
 
Topics:
AI Application, Deployment & Inference, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8614
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Abstract:

More graphics and compute intensive than its predecessors, Windows 10 is posing new challenges to delivering a great user experience. In this session, we will discuss the reasons organizations are including GPU in their Windows 10 VDI projects. We’ll share performance and cost data that will aid your organization’s Windows 10 evaluation and help you to identity the right amount of GPU for your digital employees.

More graphics and compute intensive than its predecessors, Windows 10 is posing new challenges to delivering a great user experience. In this session, we will discuss the reasons organizations are including GPU in their Windows 10 VDI projects. We’ll share performance and cost data that will aid your organization’s Windows 10 evaluation and help you to identity the right amount of GPU for your digital employees.

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Topics:
GPU Virtualization
Type:
Talk
Event:
Citrix Synergy
Year:
2017
Session ID:
CIT1707
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Abstract:

Data is changing the way companies do business, driving demand for data scientists and increasing complexity in their workflows. NVIDIA virtual GPU solutions in the data center and the cloud maximizes productivity and performance for data processing, machine learning, and a variety of other data science workloads. NVIDIA RTX capable GPUs and NVIDIA virtualization software along with VMware vSphere provide data scientists the performance they need to transform massive amounts of data into insights and create amazing user experiences in a virtual environment. Learn how you can use NVIDIA RAPIDS for executing end-to-end data science training pipelines using VMware ESXi hypervisor powered by NVIDIA virtual GPU solutions. Bring the power of power of GPU acceleration and maximize data science productivity of your data centers today.

Data is changing the way companies do business, driving demand for data scientists and increasing complexity in their workflows. NVIDIA virtual GPU solutions in the data center and the cloud maximizes productivity and performance for data processing, machine learning, and a variety of other data science workloads. NVIDIA RTX capable GPUs and NVIDIA virtualization software along with VMware vSphere provide data scientists the performance they need to transform massive amounts of data into insights and create amazing user experiences in a virtual environment. Learn how you can use NVIDIA RAPIDS for executing end-to-end data science training pipelines using VMware ESXi hypervisor powered by NVIDIA virtual GPU solutions. Bring the power of power of GPU acceleration and maximize data science productivity of your data centers today.

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Topics:
GPU Virtualization
Type:
Talk
Event:
VMWorld
Year:
2019
Session ID:
VM9063
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