====== Jetson AGX Orin Development ======

==== Download SDKmanager in Host(X86 PC) ====
https://developer.nvidia.com/sdk-manager\\


==== Console mode flash command ====

Before JetPack 5.1.1\\
Jetson Orin module to be emulated	Flashing command\\
Jetson AGX Orin 64GB	           sudo ./flash.sh jetson-agx-orin-devkit mmcblk0p1\\
Jetson AGX Orin 32GB	           sudo ./flash.sh jetson-agx-orin-devkit-as-jao-32gb mmcblk0p\\
Jetson Orin NX 16GB	           sudo ./flash.sh jetson-agx-orin-devkit-as-nx16gb mmcblk0p1\\
Jetson Orin NX 8GB	           sudo ./flash.sh jetson-agx-orin-devkit-as-nx8gb mmcblk0p1\\
Jetson Orin Nano 8GB*	           sudo ./flash.sh jetson-agx-orin-devkit-as-nano8gb mmcblk0p1\\
Jetson Orin Nano 4GB	           sudo ./flash.sh jetson-agx-orin-devkit-as-nano4gb mmcblk0p1\\


After JetPack 5.1.2\\
sudo ./flash.sh jetson-agx-orin-devkit internal\\


==== Install Vscode ====

$ git clone https://github.com/JetsonHacksNano/installVSCode.git\\
$ cd installVSCode\\
$ ./installVSCode.sh\\

./installVSCodeWithPython.sh\\

code

Jetpack 5.x會有無法啟動的問題
安裝後執行以下程式碼即可啟用(參考來源)

code --no-sandbox

==== Install Chromium ====

search ubuntu SW "chromium"


==== Install JetPACK ====
cat /etc/nv_tegra_release\\
sudo apt update\\
sudo apt dist-upgrade\\
sudo reboot\\
sudo apt install nvidia-jetpack\\


==== Install JTOP ====
sudo apt install python3-pip\\
sudo pip3 install jetson-stats\\
sudo systemctl restart jtop.service\\

sudo jtop\\

jetson_release 命令显示NVIDIA Jetson的状态和所有信息\\
tegrastats 命令行查看各资源信息\\


minicom -D /dev/ttyACM0\\


==== Setting CPU clock to maximum ====

Setting AGX ORIN development kit Power mode at the upper right corner 
MAXN 50W 30W 15W

If you want to run CPU maximum frequency\\
$sudo jetson_clocks\\

Using Jetson Power GUI\\
  


https://developer.nvidia.com/deepstream-getting-started\\
https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_Quickstart.html#jetson-setup\\



==== Deepstream ====

/opt/nvidia/deepstream/deepstream-6.3/samples\\



$ sudo apt install \
libssl1.1 \
libgstreamer1.0-0 \
gstreamer1.0-tools \
gstreamer1.0-plugins-good \
gstreamer1.0-plugins-bad \
gstreamer1.0-plugins-ugly \
gstreamer1.0-libav \
libgstreamer-plugins-base1.0-dev \
libgstrtspserver-1.0-0 \
libjansson4 \
libyaml-cpp-dev


=== 1. Clone the librdkafka repository from GitHub: ===

$ git clone https://github.com/edenhill/librdkafka.git\\

=== 2. Configure and build the library: ===

$ cd librdkafka\\
$ git reset --hard 7101c2310341ab3f4675fc565f64f0967e135a6a\\
$ ./configure\\
$ make\\
$ sudo make install\\

=== 3. https://catalog.ngc.nvidia.com/orgs/nvidia/resources/deepstream ===

Get deepstream-6.3_6.3.0-1_arm64.deb for Jetson not to download for x86\\
$ sudo apt-get install ./deepstream-6.3_6.3.0-1_arm64.deb\\

=== 4. Copy the generated libraries to the deepstream directory: ===

$ sudo mkdir -p /opt/nvidia/deepstream/deepstream-6.3/lib\\
$ sudo cp /usr/local/lib/librdkafka* /opt/nvidia/deepstream/deepstream-6.3/lib\\


==== Running deepstreaming demo ====


sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source30_1080p_dec_infer-resnet_tiled_display_int8.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source30_1080p_dec_preprocess_infer-resnet_tiled_display_int8.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt

XXXX sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8_gpu1.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source1_usb_dec_infer_resnet_int8.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source2_1080p_dec_infer-resnet_demux_int8.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.yml

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source30_1080p_dec_infer-resnet_tiled_display_int8.yml

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source4_1080p_dec_preprocess_infer-resnet_preprocess_sgie_tiled_display_int8.txt

sudo deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source2_dewarper_test.txt


==== CPU Stress Test ====
sudo apt update\\
sudo apt install cuda-toolkit-11-4\\
sudo apt install stress\\
sudo apt -y install pip\\
sudo apt -y install python3-pip\\
sudo -H pip install -U jetson-stats\\


compiled jetson-gpu-burn source code\\

git clone https://github.com/anseeto/jetson-gpu-burn.git\\
cd jetson-gpu-burn\\
make\\
 
Using stress to run CPU loading\\
Using gpu_burn to run GPU loading\\


running CPU：8 cores\\
$stress -c 8 &\\
running CPU：12 cores\\
$stress -c 12 &\\
running GPU maximum loading：\\
$./gpu_burn 1000\\