Category: Ubuntu

jetson nano, baby steps

whbeebe
Ubuntu 18.04 desktop running on the Jetson Nano and LG 34UM61 monitor

I turned 66 earlier this month and in the process hit official retirement age. Guys who are rich enough usually go out and get something really blingy, like a new set of golf clubs or a deep sea fishing set, or something equally expensive and self-indulgent. Me, I went out and spent a whole $99 on the Jetson Nano. I figured if I was going to be “retired” then I’d go back in time and work with what got me started many decades ago, an embedded system. I started out as an electrical engineer and wrote assembly language drivers and test routines for embedded systems. As time went along, I drifted deeper into writing software as the hardware side of the business moved out of Atlanta and to places like Dallas and Silicon Valley. I never went with them because I’d traveled to those places and they weren’t as enjoyable as Atlanta and the South. And I can’t knock software development as it helped pay the bills and raise a family. Now I don’t need to do that anymore and I can go back and do what really scratches my intellectual itches.

This embedded system is a whole lot different, and a whole lot more powerful, than the embedded systems I stared with in the early 1980s. Everything about the Jetson Nano is incredibly advanced from the systems available in the 1980s, starting with the 64-bit quad core ARM processor to the 128 core nVidia graphics co-processor being used for machine learning. And all for a mere $99. And I mean that. The kind of processing power and hardware resources on this board would have ranged from outlandishly expensive to impossible to obtain.

The operating system that is available with this board, a targeted version of open source Ubuntu 18.04 LTS compiled for the ARM Cortex-A57, would have cost additional thousands and been closed source with an NDA to sign on top of that.

This $99 board is a remarkable bargain of a computer. I’ve read the reviews of frustrated users who gave it one star talk about how difficult it to set up and operate. So far my experience has been nearly 100% trouble free. I’ve had a few minor bumps, but it’s been after getting the OS up and running and configuring the system. Experiences so far with this board have been as satisfying, if more so, than all my experiences with the Raspberry Pi from 2 to 4.

Now that I’m “retired” I’ll be dabbling in the uses for this board, as well as with all the other little bits and bobs I’ve been collecting now for some number of years. I’ll be able to sit back and move at my own speed without having to put it aside because I needed to go to sleep and then into work the next morning. I’m an inveterate tinkerer, and Jetson Nano is the ultimate tinkerer’s tool and toy.

running with google’s coral accelerator with raspberry pi 4

whbeebe


Continuing with the same 2GB Raspberry Pi I used to try out Ubuntu for IoT, I reloaded it with Raspbian Buster and plugged Google’s Coral Accelerator. I’d gotten it yesterday for $75 from Amazon. The Raspberry Pi 4 comes with two USB 3 ports and a reasonably up-to-date and fast quad-core CPU. I had given serious consideration to purchasing Nvidia’s Jason Nano, but it came with its own support SBC with a CPU no better than a Raspberry Pi 3, and to top it off I’d have had to install and learn the peculiar ways of yet another Linux distribution for the Nano. The monitory difference between the Coral and the Nano is inconsequential; the cost is the much larger investment in time required to master yet another Linux system as well as using the Nvidia GPU. I have neither the time nor patience for that anymore. Give me something that I can quickly plug into and use with what I already have.

Getting set up and running was super fast. It took about 15 minutes to go online for the setup directions, install the Coral support libraries, git clone an example, plug in the Coral, and then run the example. The example ran successfully. All the steps where very straightforward and fast.

I then decided to run a secound example, this time Google’s detection example.


It’s difficult to see if you don’t zoom into the screen capture, but if you do you will see Admiral Grace Hopper’s tie is identified and a red box drawn around it. This is test #2, and a bit more interesting than the first test.

Not much more to offer at this point as all I’m doing is pulling the examples and giving them a spin. I’ll work on writing something more original when I better understand the system. Fortunately all the higher level software is written in Python. For me it’s a joy to work with Python, especially version 3, on any system.

Hopefully more to come.