2.Network configuration and Jtop

Jtop installation

(1) Installing JTOP to check CPU usage

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sudo apt-get update
sudo apt-get full-upgrade
sudo apt install curl
sudo apt install nano
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py 
sudo python3 get-pip.py 
sudo pip3 install jetson-stats
jtop

Check the installed system components

(1) The OS image of Jetson nano already comes with JetPack, cuda, cudnn, opencv, and other installed examples. The installation path for these examples is as follows

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TensorRT /usr/src/tensorrt/samples/
CUDA /usr/local/cuda-10.2/samples/
cuDNN /usr/src/cudnn_samples_v8/
VisionWorks /usr/share/visionworks/sources/samples/
/usr/share/visionworks-tracking/sources/samples/
/usr/share/visionworks-sfm/sources/samples/

OpenCV /usr/share/opencv4/samples/

(2) Check that CUDA version 10.2 is already installed in CUDA Jetson nano, but if you run nvcc - V at this time, it will not succeed. You need to write the path of CUDA to the environment variable. The Vim tool comes with the OS, so run the following command to edit the environment variables.

Check if there is nvcc in the bin directory of cuda:

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ls /usr/local/cuda/bin

If present,

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sudo vim ~/.bashrc  Enter the configuration file; Add the following two lines on the last side:

Note: In vim, use Esc to return to command mode, and switch to the input module through I to enter text in input mode

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export PATH=/usr/local/cuda/bin:$PATH

export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

Note: After exiting the command mode through Esc, press: to start inputting commands, wq to save and exit, q to exit, q! For forced exit Save to exit.

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source ~/.bashrc

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beckhans@Jetson:~$ nvcc -V

(3) Check OpenCV OpenCV4.1.1 version is already installed in Jetson nano. You can use the command to check if OpenCV is installed properly

pkg-config opencv4 --modversion

If OpenCv is installed properly, the version number will be displayed, and my version is 4.4.1

(4) Check cuDNN

CuDNN has been installed in Jetson nano and there are examples available for operation. Let's run the examples to verify the CUDA above.

Enter jtop at the terminal, press the right arrow key on the keyboard to select * * 7info * *, and you can see the version of cuDNN, as shown in the following figure.