Use Jtop

Install Jtop

(1) Install JTOP to check the 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 # Download the installation script
sudo python3 get-pip.py # Run the installation script
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, etc., which are already installed, and there are examples. The installation paths of these examples are 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/
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OpenCV /usr/share/opencv4/samples/

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

First, check whether there is nvcc in the bin directory of cuda:

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ls /usr/local/cuda/bin

If it exists,

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sudo vim ~/.bashrc enters the configuration file; Add the following two lines at the end:

Note: In vim, return to command mode by pressing Esc, switch to input module by pressing I, and enter text in input mode

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

Note: After exiting to command mode via Esc, press : to start entering commands, wq for save and exit, q for exit, and q! for forced exit

Save and exit.

Then you need to source it to take effect.

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source ~/.bashrc

After source, execute nvcc -V again. The result is as follows

beckhans@Jetson:~$ nvcc -V

(3) Check OpenCV

OpenCV 4.1.1 has been installed in Jetson-nano. You can use the command to check whether OpenCV is installed properly

pkg-config opencv4 --modversion

If OpenCV is installed properly, the version number will be displayed. My version is 4.4.1

(4) Check cuDNN

cuDNN has been installed in Jetson-nano, and there are examples to run. Let's run the example to verify the above CUDA

• Enter jtop in 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: