側欄
目錄表
Jetson AGX Orin Development
Download SDKmanager in Host(X86 PC)
Orin AGX Platform Adaptation and Bring-Up Guide
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
Flash AGX ORIN Development Kit
sudo ./flash.sh jetson-agx-orin-devkit internal
Build Kernel
export CROSS_COMPILE_AARCH64_PATH=$HOME/l4t-gcc/ export CROSS_COMPILE_AARCH64=$HOME/l4t-gcc/bin/aarch64-buildroot-linux-gnu- cd ~/workspace/NX/Linux_for_Tegra/source/public mkdir kernel_out ./nvbuild.sh -o $PWD/kernel_out cd ../../ ./fl.sh
Install Vscode on Target Device
git clone https://github.com/JetsonHacksNano/installVSCode.git cd installVSCode ./installVSCode.sh ./installVSCodeWithPython.sh code --> run vscode from console mode
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
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. Get deepstream-6.3_6.3.0-1_arm64.deb
Download deepstream-6.3_6.3.0-1_arm64.deb
Get deepstream-6.3_6.3.0-1_arm64.deb for Jetson not to download for x86
sudo apt 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
Fan Control
/etc/nvfancontrol.conf
FAN_DEFAULT_PROFILE cool
Restart the service
sudo systemctl restart nvfancontrol
Power Mode Setting
Nvidia Power Model Tool to config ID=0 “MAXN”
sudo nvpmodel -m 0(MAXN)/1(15W)/2(30W)/3(50W)
Set static max frequency to CPU, GPU and EMC clocks
sudo jetson_clocks
AGX Stable Diffusion
git clone https://github.com/chitoku/stable-diffusion cd stable-diffusion git checkout jetson cp ~/Downloads/sd-v1-4.ckpt /home/aopen/stable-diffusion/models/ldm/stable-diffusion-v1/ ./docker/run.sh python3 scripts/txt2img.py --prompt "Robots marching down a street in Japanese city" --plms
JETSON AGX Orin performance test
https://github.com/NVIDIA-AI-IOT/jetson_benchmarks
git clone https://github.com/NVIDIA-AI-IOT/jetson_benchmarks.git\\ cd jetson_benchmarks\\ mkdir models\\ sudo sh install_requirements.sh\\ python3 utils/download_models.py --all --csv_file_path ./benchmark_csv/orin-benchmarks.csv --save_dir /home/aopen/jetson_benchmarks/models\\ sudo python3 benchmark.py --all --csv_file_path benchmark_csv/orin-benchmarks.csv --model_dir /home/aopen/jetson_benchmarks/models\\
Where is DTSI file
/home/ubuntu/workspace/dev2725/Linux_for_Tegra/source/public/hardware/nvidia/platform/t23x
AGX ORIN Development Kit Flash flow
sudo ./flash.sh jetson-agx-orin-devkit internal flash.sh # Num 1688 code start & entry jetson-agx-orin-devkit.conf --> Define the DTB & SOM p3701.conf.common --> SOM Define
Disable Board ID EEPROM
File Location : Linux_for_Tegra/bootloader/tegra234-mb2-bct-common.dtsi (the MB2 BCT file) Modification: - cvb_eeprom_read_size = <0x100> + cvb_eeprom_read_size = <0x0>
Modified
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/t186ref/BCT/tegra234-mb2-bct-scr-p3701-0000.dts
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/tegra234-mb2-bct-common.dtsi
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/source/public/hardware/nvidia/platform/t23x/common/kernel-dts/t234-common-cvm/tegra234-cvm-p3701.dtsi --> Serial port
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/source/public/hardware/nvidia/platform/t23x/concord/kernel-dts/tegra234-p3701-0000-p3737-0000.dts --> hdmi / hpd pin
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/tegra234-mb2-bct-common.dtsi --> eeprom size 0
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/tegra234-mb1-bct-gpio-p3701-0000-a04.dtsi --> GPIO setting
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/t186ref/BCT/tegra234-mb1-bct-pinmux-p3701-0000-a04.dtsi --> pinmux
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/bootloader/t186ref/BCT/tegra234-mb1-bct-padvoltage-p3701-0000-a04.dtsi --> padvoltage
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/p3701.conf.common --> process_chip_sku_version() / ODMDATA
LAN
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/p3701.conf.common
ODMDATA="gbe-uphy-config-22,hsstp-lane-map-3,nvhs-uphy-config-0,hsio-uphy-config-16,gbe0-enable-10g";
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/source/public/hardware/nvidia/platform/t23x/concord/kernel-dts/cvb/tegra234-p3737-pcie.dtsi
/DonRtest
pcie@14180000 {
status = "okay";
phys = <&p2u_hsio_0>;
phy-names = "p2u-0";
};
/home/ubuntu/workspace/dev2725o/Linux_for_Tegra/source/public/kernel/kernel-5.10/arch/arm64/configs/defconfig
# TPM
CONFIG_HW_RANDOM_TPM=y
CONFIG_ARCH_BCM2835=y
CONFIG_HW_RANDOM_BCM2835=m
CONFIG_SPI_BCM2835=y
CONFIG_SECURITYFS=y
CONFIG_TCG_TPM=y
CONFIG_TCG_TIS_CORE=y
CONFIG_TCG_TIS_SPI=y
CONFIG_DEVPORT=y
CONFIG_HW_RANDOM=m
Check HDMI Status
xrandr --output HDMI-0 --mode <res> --rate <refresh_rate> ex: xrandr --output HDMI-0 --mode 1280x720 --rate 60
Pinmux Changes
If your carrier board schematic differs from that of the reference carrier board in Jetson Xavier NX Developer Kit, you must change the pinmux configuration applied by the software.
To define your board’s pinmux configuration, download the Jetson Xavier NX pinmux table from the Jetson Download Center. Be sure to get the right version of the table for your SOM.
The pinmux table is a spreadsheet that:
- Shows the locations and default pinmux settings
- Acts as a data source for software that defines the pinmux settings in the source code or device tree
You must customize the spreadsheet for the configuration of your board, then convert the .dtsi file generated by Excel to a .cfg file. For instructions, see the README file at:
Linux_for_Tegra/kernel/pinmux/t19x/ You must perform the same conversion for gpio.dtsi and padvoltage.dtsi.
GPIO Changes
If you designed your own carrier board, to translate from SOM connector pins to actual GPIO numbers you must understand the GPIO mapping formula below. The translated GPIO numbers can be controlled by the driver.
To check a GPIO number This example procedure checks the GPIO number of signal name SPI0_CS1.
- Open the Jetson AGX Orin pinmux table. (See Pinmux Changes, above.)
- Search the table for SPI0_CS1.
- Confirm that the Customer Usage field contains the GPIO name GPIO3_PZ.07.
- Search PZ.07 using the following command:
cat /sys/kernel/debug/gpio | grep PZ.07
