Below are my personal notes related to the Nvidia Jetson Nano Dev-board.
Nvidia allows your to fine tune the performance of your Jetson nano. More on this here.
sudo /usr/bin/jetson_clocks.sh --show
Raffaello Bonghi rbonghi
🤖
bgulla
/ jetson_nano_cheatsheet.md
Last active
September 5, 2022 21:29
Notes related to the NVIDIA Jetson Nano dev kit
JasonAtNvidia
/ txdocker
Last active
March 8, 2022 08:15
Short Bash script to enable use of the GPU within a docker container running on an NVIDIA Jetson TX2. Place inside /usr/local/bin/, chmod +x txdocker, ensure it is in your system PATH, and use just as you would the docker command.
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| #!/bin/bash | |
| #Jason T. 2-6-2018 | |
| # Check specifically for the run command | |
| if [[ $# -ge 2 && $1 == "run" ]]; then | |
| # Tell docker to share the following folders with the base system | |
| # This allows the docker containers to find CUDA, cuDNN, TensorRT | |
| LIB_MAPS="/usr/lib/aarch64-linux-gnu \ | |
| /usr/local/cuda \ | |
| /usr/local/cuda/lib64" |
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| #define BIT_LEN 7 | |
| float line_value(int line) { | |
| int i; | |
| int value = 0, count = 0; | |
| for(i=0; i < BIT_LEN; ++i) { | |
| int mask = (1 << (i)); | |
| if((line & (mask)) == (mask)) { | |
| value += i: | |
| count++; |