Hi
Continues this topic https://devtalk.nvidia.com/default/topic/1069371/tensorrt/yolov3-fps-on-tensorrt/.
In this link: https://devblogs.nvidia.com/jetson-xavier-nx-the-worlds-smallest-ai-supercomputer/, report inferencing FPS is close to 100 FPS of YOLO-V3(608x608) on AGX Xavier with TensorRT.(Figure 3)
we try more method in this issue topic link https://devtalk.nvidia.com/default/topic/1069371/tensorrt/yolov3-fps-on-tensorrt/
, but not solve this problem, so we create new topic focus on “How to use GPU + 2 DLA can be 100FPS for YoloV3 on Xavier”.
So far we have tried to use GPU+2DLA follow command:
sudo nvpmodel -m 0
sudo jetson_clocks
Terminal 1 command:
./trtexec --onnx='yolov3.onnx' --workspace=26 --int8 --useSpinWait --iterations=100
Terminal 2 command:
./trtexec --onnx=yolov3.onnx --workspace=30 --int8 --useSpinWait --iterations=100 --useDLACore=0 --allowGPUFallback
Terminal 3 command:
./trtexec --onnx=yolov3.onnx --workspace=26 --int8 --useSpinWait --iterations=100 --useDLACore=1 --allowGPUFallback
and result of FPS in this figure
Can the official provide actual example code?
Because this problem has been going on for a long time.