JetsonHacks

Developing on NVIDIA® Jetson™ for AI on the Edge

NVIDIA SDK Manager for Jetson – JetPack 4.2

The NVIDIA SDK Manager installs the operating system, libraries and SDKs on the Jetson Developer Kits. Looky here:

Background

When NVIDIA introduces a new Jetson model, they usually come out with a new revision of JetPack to support it. In this case it is the Jetson Nano Developer Kit. However with the new JetPack 4.2, NVIDIA is also introducing the SDK Manager.

The SDK Manager is a completely new, much improved installer which runs under Ubuntu 16.04 or 18.04 on a PC. JetPack now refers to the collection of OS, libraries and tools which run on the Jetson platform.

Note: If you have a Jetson Nano and simply are trying to create a SD card, follow the procedure to download a disk image and flash the SD card directly.

JetPack Information

The SDK Manager may be used to install the development tools on a Jetson Development Kit, either a Jetson AGX Xavier, TX2, TX2i, or Nano. You can read more information on the JetPack web page. There’s a list of all of the System Requirements, as well as the different tools that can be installed.

Note

In addition to a Jetson, you will need another desktop or laptop computer with an Intel or AMD x86 processor. These types of machines are commonly called a PC for Personal Computer. This computer is referred to as the host for the flashing process. JetPack is an x86 binary and will not run on an ARM based machine like the Jetson. In the video, a Dell laptop is being used as the host.

Installation

For the most part, installation pretty easy. From an Ubuntu 16.04 PC or 18.04 64 bit host computer, you simply download the JetPack software from the NVIDIA web link above (you’ll have to sign in with your developer account to download JetPack) and follow the instructions in the setup guide.

The NVIDIA instructions are quite wonderful now. You should not have any issues following them.

The set of tools that you can install is flexible. You have the option to install a cross compiler on the host for building your Jetson programs on your PC.

Installation from the demo host computer to the Jetson took about an hour fifteen all together, including all the downloads on a 30 MBs Internet link, flashing the Jetson.

One thing I did notice in the setup, if ‘Automatic’ is chosen to set the Jetson into recovery mode and the Jetson has a version 3.X version running, then there may be issues like the Jetson doesn’t go into force recovery mode.

In the video, we set the Jetson TX2 into force recovery mode manually. Note: You do not need to have the Jetson connected to a network for the install, only the USB connection to the host computer using the micro USB connector. This is different from previous versions of the JetPack installer.

A nice new addition is the ability to download all of the images and supporting libraries, and then flash the Jetson offline.

Note: Some of the virtual machines just won’t work with JetPack.

Note: On the Jetson Nano, the procedure to enter recovery mode is different. Refer to the installation manual for details.

Tools Available

Here are some of the JetPack release highlights for the version 4.2:

  • Linux for Tegra (L4T) 32.1.0
  • LTS Kernel 4.9
  • TensorRT
  • cuDNN
  • VisionWorks
  • CUDA 10.0
  • Multimedia API
  • OpenCV

Developer Tools

  • Tegra Graphics Debugger
  • Tegra System Profiler 
  • PerfKit 

Samples

Here’s how to install some of the JetPack 4.2 samples. Looky here:

Do I have to have an Ubuntu PC?

The short answer is yes. You may be able to use a VM, but it is not officially supported. Here’s what NVIDIA wrote in the Jetson Forum:

The flashing must be performed from within 64-bit Linux on an x86-based machine. Running an Ubuntu x86_64 image is highly-recommended for the flashing procedure. If you don’t already have a Linux desktop, and are trying to avoid setting up dual-boot, you can first try running Ubuntu from within a virtual machine. Although convenient, flashing from VM is technically unsupported — warning in advance that while flashing from within VM, you may encounter issues such as the flashing not completing or freezing during transfer. Chances will be improved if you remove any USB hubs or long cables in between your Jetson and the host machine.

The next logical step would be to boot your desktop/laptop machine off Ubuntu LiveCD or USB stick (using unetbootin tool or similar). 

Finally, if you have an extra HDD partition, you can install Ubuntu as dual-boot alongside Windows. Flashing natively from within Ubuntu is the supported and recommended method for flashing successfully. It may be wise to just start in on dual-boot from the get-go, otherwise you may end up wasting more time trying to get the other (potentially more convenient, but unsupported) methods to work.

If you encounter issues, please ask questions on the Jetson & Embedded Systems development forums.

Conclusion

The first time through, setting up the system and flashing the Jetson can take around a little more than an hour or so depending on your download speeds and the speed of your PC. In the video, a simple cable modem 30MBs was used for downloading. Downloading all of the components only happens the first time you do an installation, subsequent installations check for updates and if none are available then simply flash the Jetson, saving a lot of time.

Facebook
Twitter
LinkedIn
Reddit
Email
Print

13 Responses

  1. Hi, I’m using SDK Manager 4.2 (and have tried earlier versions too) for Xavier with ConnectTech Rogue. I have to interrupt the process at the flash stage to overlay the connecttech BSP but all of that generally works OK and I can flash and boot up the Xavier. However, if I then continue the process and install CUDA and OpenCV from the SDK Manager, OpenCV does not appear to support CUDA (i.e. c++ programs don’t compile if they use cuda:: and cv::getBuildInformation() reports no CUDA support. I’ve already asked this question on nvidia forums but the nvidia guys seem to think I am wrong! Any ideas???

    1. My understanding is that the version of OpenCV supplied by the SDK Manager does not support CUDA (or gstreamer for that matter) out of the box. There are various scripts to build it, depending if you want a 3.X version or a 4.X version of OpenCV. Do you have a link to the forum where you asked your question?

      1. Thank you for the confirmation – I am not going mad afterall! The thread is at https://devtalk.nvidia.com/default/topic/1057321/jetson-agx-xavier/sdk-manager-opencv-cuda-support/post/5364829/#5364829

        I have used your script for building/installing OpenCV with CUDA and it has really helped – many thanks 🙂 I should add that with L4T 4.2 it was necessary to install the SDK components from sdk manager then purge opencv first otherwise the script does not find CUDA during the pre-build checks.

  2. Hi, I´m using the jetson tx2 module with the j121 carrier board from auvidea. In adition I´m using ubuntu 18.04. I flashed the jetson succesfully, but after fleshing the sdkmanager is telling me: Could not detect Nvidia Jetson device connected to USB. So I´m not able to install the other components on my jetson.

  3. sir i am using jetpack 4.5.1. i get error ehile installing computer vision sdk component- opencv part. how can i resolve error. i m using ubuntu 16.04

  4. Hi sir,
    I received an error when installing SDK components after flash AGX Xavier.
    Do you recommend anything to solve this problem?
    Thanks for your interest.

    SUMMARY: CUDA Toolkit for L4T: Failed to install debian package for apt issues, requires manual fix [host]. SDK Manager received errors while using apt commands on your system. Please check that the Ubuntu local apt repository is working well on your local system including dependencies of packages. Review SDK Manager terminal for the specific error/s.

Leave a Reply

Your email address will not be published. Required fields are marked *

Disclaimer

Some links here are affiliate links. If you purchase through these links I will receive a small commission at no additional cost to you. As an Amazon Associate, I earn from qualifying purchases.

Books, Ideas & Other Curiosities