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Computer Vision 3D Flow and Function AI with LiDAR
Introduction Solution overview Partner overview Architecture overview Sizing and scaling
Sizing and scaling
Sizing the solution
GPU requirements Sizing approach for LiDAR Sizing the SENSR nodes Storage sizing Network sizing
Scaling the solution
Adding LiDAR processing Future considerations
Use case validation Conclusions References

Sizing the solution

Home > Workload Solutions > Computer Vision > White Papers > Computer Vision 3D Flow and Function AI with LiDAR > Sizing the solution

Sizing the solution

  • Sizing approach for LiDAR

    It is very challenging to size universally for LiDAR streams. This is because the following items impact the system resources required:

    • The density of points produced by the LiDAR sensor
    • The size of the coverage area that requires object detection analytics
    • The number of LiDAR sensors positioned to collect data that will cover the scene

    We followed the common practice of testing sizing based on how many LiDAR points per second can be processed while monitoring the latency in the system.

    For this sizing exercise, the simulated LiDAR sensors were each publishing at a rate of 1.2 million points a second. Up to four sensors were running on an Algo node at any given time to give a maximum of 4.8 million points being processed per second.