• Hardware Platform (Jetson / GPU) :Jetson Xavier NX
• DeepStream Version :5.1
• JetPack Version (valid for Jetson only) : 4.5
• TensorRT Version : 7.1.3
I create a gstreamer pipline that have 3 part of infernce, one part is pgie and two other parts are sgie.
My pipeline is like this :
Sources >> nvinfer-PGIE(detection) >>> nvinfer-SGIE(detection) >>> nvinfer-SGIE(classifier) >> sinks
I converted each of models on GPU and also I used queue element after and before of each element for none-blocking of each parts and works independent from each other. This solution is only used GPU engine for three engines, but the jetson nx also has 2-DLAs engines.
1- I want to know how I can use these three models for each engine to work Independent from each other?
I don’t want to work these part like sequential.
2- If I convert the pgie engine on GPU and two others sgie engine on 2-DLAs, So the pipeline runs three models Independent from each other like parallel? or again runs as sequential mode? If runs sequential, So what’s advantage of DLAs used in jetson when GPU run faster than DLAs?