Jetpack is an SDK that basically contains everything needed for deep learning and AI applications in a handy package bundle containing the OS for for the Xavier. Installation on the Xavier requires downloading and flashing the image to a MicroSD card.
We are working on sourcing discount codes for the Jetson Xavier NX Developer Kit and hope to have them available the week before classes start. For details on set up see homework 1:
- Jetson Xavier NX Developer Kit
- MicroSD card (64GB minimum size)
- USB MicroSD card reader
- NVMe M.2 SSD (256GB minimum size) NOTE: SATA M.2 SSDs will not work
- Size 0 Philips head screwdriver
- Micro USB to USB cable
- USB Webcam
On your Windows, Mac, or Ubuntu workstation, navigate to the Jetpack homepage and click on "Download SD Card Image" in the JETSON XAVIER NX DEVELOPER KIT box. Once it downloads, follow the steps at Getting Started with Jetson Xavier NX Developer Kit to flash the SD card.
NVIDIA provides flashing instructions for Windows, Linux, and Mac. You will need to insert the MicroSD card into the card reader and connect it to the USB port on your computer.
While the flashing process runs, you can use the Philips head screwdriver to install the SSD on your Xavier NX.
A quick video showing MicroSD card and SSD installation is here.
Once the flashing process is complete, you will insert the MicroSD card into your Xavier. Do not power it on yet.
There are two setup options.
- Use a USB keyboard/mouse and HDMI display
- Use a tty terminal from Mac or Linux
With the first option, you will obviously need additional hardware. Option number two is quite easy, though, and we will walk you through the process.
If you choose option two, you will need a machine running Linux (we recommend Ubuntu 18.04), or a Mac. If you do not have one, you can create a VM running Ubuntu (see section 1.2).
If you are using install option one, you can connect the keyboard, mouse, and display to complete the setup process. Once they are connected, you can connect the power adapter. Follow the steps to complete the setup and then go to section 2. If you have issues connecting to wifi, skip that step and connect the Xavier directly to your router with an ethernet cable after the setup is complete.
If you are using install option two, you can connect the Xavier to your Mac or Linux computer using the micro-USB cable and then connect the power adapter.
If you are using a VMware VM, you will be prompted to connect the USB device to your host computer or the VM; choose the VM. When in the VM, use "lsusb" in the terminal to check if the Xavier is visible.
You will need to use a Linux VM or a Mac to perform these steps.
You get a free VMware subscription through Berkeley here. Download and install VMware Workstation (for Windows) or VMware Fusion (for macOS).
Download the Ubuntu 18.04 iso image here.
Create a new VM in VMware.
Walk-through on VMware image creation is here.
VM Configuration, the size of the disk should be 40GB absolutely minimum. Give the VM 2-4 cores to make sure cross-compilation does not take forever, and at least 4-8G of RAM.
Run this command from the Mac Terminal application:
ls -ls /dev/cu.*
You should see a usbmodem device like:
/dev/cu.usbmodem14210200096973
You will use the screen command to connect to the tty device:
screen /dev/cu.usbmode* 115200 -L
Run this command from the Linux terminal application:
ls -ls /dev/ttyA*
You should see a ttyACM device like:
/dev/ttyACM0
You will use the screen command to connect to the tty device:
sudo apt-get update
sudo apt-get install -y screen
sudo screen /dev/ttyACM0 115200 -L
Note: the wifi configuration might not work due to a bug in the software. If it is an issue, just skip the wifi step and connect the Xavier directly to your router with an ethernet cable after the setup is complete
You will finish the setup process using the tty terminal you just opened to the device.
It is highly recommended that you connect your Xavier directly to your router with an ethernet cable.
You can have a keyboard, mouse, and monitor attached to your Jetson; but it is also extremely convenient to set up screen sharing, so you can see the Jetson desktop remotely. This is needed, for instance, when you want to show Jetson's screen over a web conference - plus it's a lot easier than switching between monitors all the time.
- Get a VNC screen sharing client. You can install TightVNC, Remmina, or another VNC client of your choice.
- Configure your Xavier for remote screen sharing.
On your Xavier, open a terminal (or ssh to your Xavier from another computer).
mkdir ~/.config/autostart
- Now, create/open the file
~/.config/autostart/vino-server.desktopand insert the following:
[Desktop Entry]
Type=Application
Name=Vino VNC server
Exec=/usr/lib/vino/vino-server
NoDisplay=true
- Disable security by running the following from the command line:
gsettings set org.gnome.Vino prompt-enabled false
gsettings set org.gnome.Vino require-encryption false
- Enable automatic login by editing /etc/gdm3/custom.conf and add the following (the AutomaticLogin ID should be the user ID you created in the setup):
# Enabling automatic login
AutomaticLoginEnable = true
AutomaticLogin = nvidia # Ensure that you replace 'nvidia' with the ID you use to login to your Xavier
- Reboot your Xavier
- Then, launch your remote sharing client, choose VNC as the protocol, type in the IP address of your jetson and port 5900.
NOTE: To find your IP address, use the following command:
nvidia@xavier:~$ ip addr show | grep inet
inet 127.0.0.1/8 scope host lo
inet6 ::1/128 scope host
inet 192.168.11.103/24 brd 192.168.11.255 scope global dynamic noprefixroute eth0
inet6 fe80::4ab0:2dff:fe05:a700/64 scope link noprefixroute
nvidia@xavier:~$
The IP address in this example is on the third line: 192.168.11.103.
On any platform, you can download a VNC Viewer (like Real VNC) and use it:
and
On Linux, you can use Remmina:
- The default resolution is very small. You can change it with this command (required after every reboot):
sudo xrandr --fb 1600x900 # you can choose some other resolution if desired
Ensure the Xavier is on and running Ubuntu. Use this command to verify that everything is happy and healthy:
sudo nvpmodel -q --verbose
The output should be similar to:
NVPM VERB: Config file: /etc/nvpmodel.conf
NVPM VERB: parsing done for /etc/nvpmodel.conf
NV Fan Mode:quiet
NVPM VERB: Current mode: NV Power Mode: MODE_15W_6CORE
2
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_0: PATH /sys/devices/system/cpu/cpu0/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_1: PATH /sys/devices/system/cpu/cpu1/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_2: PATH /sys/devices/system/cpu/cpu2/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_3: PATH /sys/devices/system/cpu/cpu3/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_4: PATH /sys/devices/system/cpu/cpu4/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM CPU_ONLINE: ARG CORE_5: PATH /sys/devices/system/cpu/cpu5/online: REAL_VAL: 1 CONF_VAL: 1
NVPM VERB: PARAM TPC_POWER_GATING: ARG TPC_PG_MASK: PATH /sys/devices/gpu.0/tpc_pg_mask: REAL_VAL: 2 CONF_VAL: 1
NVPM VERB: PARAM GPU_POWER_CONTROL_ENABLE: ARG GPU_PWR_CNTL_EN: PATH /sys/devices/gpu.0/power/control: REAL_VAL: auto CONF_VAL: on
NVPM VERB: PARAM CPU_DENVER_0: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_min_freq: REAL_VAL: 1190400 CONF_VAL: 1190400
NVPM VERB: PARAM CPU_DENVER_0: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu0/cpufreq/scaling_max_freq: REAL_VAL: 1420800 CONF_VAL: 1420800
NVPM VERB: PARAM CPU_DENVER_1: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu2/cpufreq/scaling_min_freq: REAL_VAL: 1190400 CONF_VAL: 1190400
NVPM VERB: PARAM CPU_DENVER_1: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu2/cpufreq/scaling_max_freq: REAL_VAL: 1420800 CONF_VAL: 1420800
NVPM VERB: PARAM CPU_DENVER_2: ARG MIN_FREQ: PATH /sys/devices/system/cpu/cpu4/cpufreq/scaling_min_freq: REAL_VAL: 1190400 CONF_VAL: 1190400
NVPM VERB: PARAM CPU_DENVER_2: ARG MAX_FREQ: PATH /sys/devices/system/cpu/cpu4/cpufreq/scaling_max_freq: REAL_VAL: 1420800 CONF_VAL: 1420800
NVPM VERB: PARAM GPU: ARG MIN_FREQ: PATH /sys/devices/17000000.gv11b/devfreq/17000000.gv11b/min_freq: REAL_VAL: 114750000 CONF_VAL: 0
NVPM VERB: PARAM GPU: ARG MAX_FREQ: PATH /sys/devices/17000000.gv11b/devfreq/17000000.gv11b/max_freq: REAL_VAL: 1109250000 CONF_VAL: 1109250000
NVPM VERB: PARAM GPU_POWER_CONTROL_DISABLE: ARG GPU_PWR_CNTL_DIS: PATH /sys/devices/gpu.0/power/control: REAL_VAL: auto CONF_VAL: auto
NVPM VERB: PARAM EMC: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/emc_iso_cap: REAL_VAL: 1600000000 CONF_VAL: 1600000000
NVPM VERB: PARAM DLA_CORE: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/nafll_dla: REAL_VAL: 1100800000 CONF_VAL: 1100800000
NVPM VERB: PARAM DLA_FALCON: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/nafll_dla_falcon: REAL_VAL: 640000000 CONF_VAL: 640000000
NVPM VERB: PARAM PVA_VPS: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/nafll_pva_vps: REAL_VAL: 819200000 CONF_VAL: 819200000
NVPM VERB: PARAM PVA_CORE: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/nafll_pva_core: REAL_VAL: 601600000 CONF_VAL: 601600000
NVPM VERB: PARAM CVNAS: ARG MAX_FREQ: PATH /sys/kernel/nvpmodel_emc_cap/nafll_cvnas: REAL_VAL: 576000000 CONF_VAL: 576000000
The Jetson line of SoCs (including the Xavier NX) has a number of different power modes described in some detail here: TX2 or Xavier. The main idea is that the lowering clock speeds on the cpu and turning off cores saves energy; and the default power mode is a low energy mode. You need to switch to a higher power mode to use all cores and maximize the clock frequency. In the upper right corner of your desktop you will see a widget that should allow you to switch between power modes. Set your power mode to MAXN; this will enable all six cores and will maximize your clock frequency. This is ok when we use our Xavier as a small desktop computer. If you decide to use your Xavier as a robotic device and become worried about the power draw, you may want to lower this setting.
Your Xavier is booting the Operating System from the MicroSD card, which is not very fast.
We recommend that you configure your system to run from the SSD instead. Follow the instructions on this page (watch the video carefully).
Steps:
Verify that the OS is booting from the Micro SD.
lsblk
Your output should show a / in the MOUNTPOINT column of the mmcblk0p1 line:
NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINT
loop0 7:0 0 16M 1 loop
mtdblock0 31:0 0 32M 0 disk
mmcblk0 179:0 0 59.5G 0 disk
├─mmcblk0p1 179:1 0 59.2G 0 part /
├─mmcblk0p2 179:2 0 64M 0 part
├─mmcblk0p3 179:3 0 64M 0 part
├─mmcblk0p4 179:4 0 448K 0 part
├─mmcblk0p5 179:5 0 448K 0 part
├─mmcblk0p6 179:6 0 63M 0 part
├─mmcblk0p7 179:7 0 512K 0 part
├─mmcblk0p8 179:8 0 256K 0 part
├─mmcblk0p9 179:9 0 256K 0 part
├─mmcblk0p10 179:10 0 100M 0 part
└─mmcblk0p11 179:11 0 18K 0 part
zram0 252:0 0 1.9G 0 disk [SWAP]
zram1 252:1 0 1.9G 0 disk [SWAP]
nvme0n1 259:0 0 465.8G 0 disk
To setup the SSD:
# Wipe the SSD
sudo wipefs --all --force /dev/nvme0n1
# Partition the SSD
sudo parted --script /dev/nvme0n1 mklabel gpt mkpart primary ext4 0% 100%
# Format the newly created partition
sudo mkfs.ext4 /dev/nvme0n1p1
# We will use the jetsonhacks scripts to move data and enable the SSD as
# the default disk
git clone https://github.com/jetsonhacks/rootOnNVMe.git
cd rootOnNVMe/
sudo ./copy-rootfs-ssd.sh
./setup-service.sh
# Reboot for the update to take effect
sudo reboot
Run the lsblk command again to verify that you are running the OS from the SSD. This time, the / should be the MOUNTPOINT for nvme0n1p1:
NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINT
loop0 7:0 0 16M 1 loop
mtdblock0 31:0 0 32M 0 disk
mmcblk0 179:0 0 59.5G 0 disk
├─mmcblk0p1 179:1 0 59.2G 0 part /media/nvidia/48fc8f75-dc2b-4a68-9673-c4cc26f9d5db
├─mmcblk0p2 179:2 0 64M 0 part
├─mmcblk0p3 179:3 0 64M 0 part
├─mmcblk0p4 179:4 0 448K 0 part
├─mmcblk0p5 179:5 0 448K 0 part
├─mmcblk0p6 179:6 0 63M 0 part
├─mmcblk0p7 179:7 0 512K 0 part
├─mmcblk0p8 179:8 0 256K 0 part
├─mmcblk0p9 179:9 0 256K 0 part
├─mmcblk0p10 179:10 0 100M 0 part
└─mmcblk0p11 179:11 0 18K 0 part
zram0 252:0 0 1.9G 0 disk [SWAP]
zram1 252:1 0 1.9G 0 disk [SWAP]
nvme0n1 259:0 0 465.8G 0 disk
└─nvme0n1p1 259:1 0 465.8G 0 part /
Use the configure_xavier.sh script in this repo to set up swap space after you have rebooted and verified that you are running your Operating System from the SSD:
git clone https://github.com/MIDS-scaling-up/v2.git
cd v2/week01/hw
chmod +x configure_xavier.sh
./configure_xavier.sh
Install jtop (a monitoring tool from https://github.com/rbonghi/jetson_stats):
sudo -H pip install -U jetson-stats
sudo reboot
# Test after reboot
jtop
Docker is a platform that allows you to create, deploy, and run applications in containers. The application and all its dependecies are packaged into one container that is easy to ship out and uses the same Linux kernel as the system it's running on, unlike a virtual machine. This makes it especially useful for compact platforms such as the Jetson.
Jetpack 4.3 has Docker pre-installed, and has an experimental nvidia-docker support.
Let's test it to see if it can run containers. Since the Jetson doesn't have the docker image 'hello-world' downloaded yet, Docker will automatically pull it online from the official repository:
docker run hello-world
Most of the work in the class will require a Docker base image running Ubuntu 18.04 with all the needed dependencies. For the first time, in July 2019, Nvidia has released an officially supported base cuda container! Please register at the Nvidia GPU Cloud and review the documentation for the base jetson container
Let's start this container:
# allow remote X connections
xhost +
# assuming that r32.4.3 is the latest version; but please check the NGC
docker run -it --rm --net=host --runtime nvidia -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix nvcr.io/nvidia/l4t-base:r32.4.3
# this should complete successfully. Run this command to verify that you are inside the Docker container
ls
# You should see the following:
# bin boot dev dst etc home lib media mnt opt proc root run sbin srv sys tmp usr var
# Now exit from the container:
exit
More on the use of this container is here
Note that our own old Docker images for the Jetsons are still available in the docker hub, e.g. w251/cuda:tx2-4.3_b132 and w251/cuda:dev-tx2-4.3_b132. As the officially supported containers mature, we expect to sunset these; but for now, we'll keep them around just in case. We keep Dockerfiles for all of our containers here for your reference.
We'll cover Docker during the in-class lab in more detail.
Please send a message on the class portal homework submission page indicating that you were able to set up your Jetson