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Abstract:

A wide area and city surveillance system solution for running real-time video analytics on thousands of 1080p video streams will be presented. System hardware is an embedded computer cluster based on NVIDIA TX1/TX2 and NXP iMX6 modules. A custom designed system software manages job distribution, resulting in collection and system wide diagnostics including instantaneous voltage, power and temperature readings. System is fully integrated with a custom designed video management software, IP cameras and network video recorders. Instead of drawing algorithm results on the processed video frames, re-encoding and streaming back to the operator computer for display, only the obtained metadata is sent to the operator computer. Video management software streams video sources independently, and synchronizes decoded video frames with the corresponding metadata locally, before presenting the processed frames to the operator.

A wide area and city surveillance system solution for running real-time video analytics on thousands of 1080p video streams will be presented. System hardware is an embedded computer cluster based on NVIDIA TX1/TX2 and NXP iMX6 modules. A custom designed system software manages job distribution, resulting in collection and system wide diagnostics including instantaneous voltage, power and temperature readings. System is fully integrated with a custom designed video management software, IP cameras and network video recorders. Instead of drawing algorithm results on the processed video frames, re-encoding and streaming back to the operator computer for display, only the obtained metadata is sent to the operator computer. Video management software streams video sources independently, and synchronizes decoded video frames with the corresponding metadata locally, before presenting the processed frames to the operator.

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Topics:
AI Application Deployment and Inference, Intelligent Video Analytics and Smart Cities
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8409
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Abstract:
The Lattice Boltzmann Method (LBM) is implemented through a finite-volume approach to perform 2-D, incompressible, and laminar fluid flow analyses on structured grids. Once the serial version is implemented and validated through the laminar 2-D lid-driven cavity problem and 2-D flow over a circular cylinder, the flow solver is accelerated on GPU by porting compute and memory bandwidth intense functions to CUDA. The CUDA accelerated implementation is compared against serial implementation and multi-threaded version running on dual Intel Xeon processors.
The Lattice Boltzmann Method (LBM) is implemented through a finite-volume approach to perform 2-D, incompressible, and laminar fluid flow analyses on structured grids. Once the serial version is implemented and validated through the laminar 2-D lid-driven cavity problem and 2-D flow over a circular cylinder, the flow solver is accelerated on GPU by porting compute and memory bandwidth intense functions to CUDA. The CUDA accelerated implementation is compared against serial implementation and multi-threaded version running on dual Intel Xeon processors.  Back
 
Topics:
Computational Fluid Dynamics
Type:
Poster
Event:
GTC Silicon Valley
Year:
2014
Session ID:
P4180
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Abstract:
A massively multi-threaded CUDA implementation of spatial resolution and dynamic range enhancement technique is presented. The implementation obtained by combining the multi-threaded super-resolution and CLAHE blocks runs at approximately 15 frames per second, resulting in near real-time performance.
A massively multi-threaded CUDA implementation of spatial resolution and dynamic range enhancement technique is presented. The implementation obtained by combining the multi-threaded super-resolution and CLAHE blocks runs at approximately 15 frames per second, resulting in near real-time performance.  Back
 
Topics:
Video and Image Processing
Type:
Poster
Event:
GTC Silicon Valley
Year:
2013
Session ID:
P3136
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