Hello Community,
I’m new to DeepLearning and want to get into this topic, especially Reinforcement Learning.
I freshly bought a JetsonTX2 and flashed it with the newest Jetpack3.3.
I also installed TensorFlow according to this instruction:
https://docs.nvidia.com/deeplearning/dgx/install-tf-jetsontx2/index.html
I want to do a Reinforcement Learning project with openAI gym but face major problems when it comes to performance of the Jetson TX2. I have some example code for the implementation of a DDPG Agent for the Pendulum-v0 environment:
https://pemami4911.github.io/blog/2016/08/21/ddpg-rl.html
However the framerate drops as soon as the agent tries to train. Even without TensorFlow running examples like the BipedalWalker-v2 Environment have an framerate around 15-20 FPS.
Checking the system monitor i can see that all 6 CPU cores are activated and working between 0 and 60 %. Also the GPU memory is around 33% (2.2 / 7.1 GB usage). According to other forums I switch the nvpmodel to mode 0 which should be the high performance one.
Output from “~/tegrastats”:
RAM 2521/7853MB (lfb 632x4MB) CPU [50%@806,0%@345,0%@345,49%@806,54%@806,50%@806] BCPU@43.5C MCPU@43.5C GPU@42C PLL@43.5C Tboard@41C Tdiode@41C PMIC@100C thermal@42.9C VDD_IN 2309/2386 VDD_CPU 462/442 VDD_GPU 230/230 VDD_SOC 461/461 VDD_WIFI 0/43 VDD_DDR 578/588
I never before worked on an NVIDIA Board before and wanted to know if this is a known problem or simply some user errors from my side.
Thx for your support