My Team is working on a project that involves processing video feeds from over 30 cameras simultaneously. We need to run multiple custom Deep Learning models on the data, and near real-time processing is a critical requirement.
Could anyone please advise on the most suitable on-prem GPU hardware server for this task? Specifically, we are looking for production grade use case where all the scenarios need to be considered, few mentioned below:
Hardware Recommendations: Which NVIDIA GPUs or hardware servers would you suggest for real-time processing of video feeds from multiple cameras (30+) while running deep learning models?
Architecture & Framework: What would be the best architecture and deep learning frameworks to support this use case? We are looking for high performance and scalability.
NVIDIA Technical Support: Could you also provide details on the technical support offerings provided by NVIDIA for such use cases?
This request is on behalf of Accenture, and we would appreciate any official guidance or support you can offer.
As per the GPU support matrix i can figure out that NVIDIA RTX A6000 or the NVIDIA A40 or P40 will be idle for the solution but wrt to “NVENC
/CHIP” number as 2-3 can the DeepStream concurrently process 20+ camera streams live using deepstream-test3 ?
If Yes, Can you share articles and repo links for DeepStream 7.0.
Also where can i find the link to the GPU to CUDA version mapping sheet.
For receiving and decoding RTSP streams, it is only related to hardware video decoder. The number of supported streams is decided by the stream format, resolution and framerate. There is performance data for 1080p@30fps encoding / decoding of different GPUs. Video Codec SDK | NVIDIA Developer