I have the 4GB version of the Nano and the 4GB Raspberry Pi. I like the Nano, but I use it mostly as a development machine and for that I would rank the 8GB Raspberry Pi at about $89 US the best deal. Substantially below that is the Nano, and almost tied is 4GB Pi. There may be cases where you absolutely need an Nvidia machine in which case I would argue for the 4GB version, but otherwise the 8GB Pi appears to be the…
Nvidia announces Jetson Nano 2GB, a single board computer
151–160 of 205 posts
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#152What are the use-cases for a GPU-accelerated single board computer?
Same as it's always been: Gaming. I bet even this $59 computer can play games surprisingly well. Obviously not modern AAA titles or anything like that, but there's many decades' worth of games it can play (including ones originally released for non-PC platforms). There's lot of interesting Pi-powered handhelds and mini-arcade setups running emulated games; this seems like it'd be significantly better at that.
No, not even close. It's embedded systems with GPU acceleration, mostly for machine learning.
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#153Honest question, why would I choose this over an "old" Android phone that I already have in my drawer?
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#154Earlier quoted context omitted.
> From my experience, 0.05% of the people who have an Ubuntu x.y chose it because of "stability promises" of the LTS release. Your experience and my experience differ greatly, then. I manage around a hundred virtual and bare-metal Ubuntu 18.04 LTS systems. Most of our docker containers (not included in the number above) are based on an Ubuntu 18.04 image because that's what we have standardized our infrastructure aro…
> We are too busy focusing on delivering value to the business there are a lot more linux users out there than business users
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#155Earlier quoted context omitted.
> The more I use linux (and I'v been for almost 15 years), the more strongly believe that using what the Linux distros provide as a development toolchain is an antipattern. Your assertion makes no sense. Let me explain why. You've adopted a LTS release which was made public 2 years ago, was already a couple of years in the making, and is aimed at establishing a solid and reliable base system that can be targetted by…
> You've adopted a LTS release which was made public 2 years ago, was already a couple of years in the making, and is aimed at establishing a solid and reliable base system that can be targetted by the whole world with confidence. From my experience, 0.05% of the people who have an Ubuntu x.y chose it because of "stability promises" of the LTS release. They just want a quick linux install to run their shit on, or it…
You might be right, that %.05 of people choosing to use LTS distros are doing so for its service promises. But I'd counter that the majority of those who care are managing hundreds or thousands of machines / users. The end users might not know that they care, and that's because the admins are doing a good job.
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#156Earlier quoted context omitted.
gcc is part of the infrastructure, for the simple reason that you need the same compiler version to build Linux kernel modules.
> for the simple reason that you need the same compiler version to build Linux kernel modules. Which kernel modules wouldn't come as precompiled packages in Ubuntu ? (real question - as an Arch user for instance I haven't had the need for DKMS for years)
[0] https://wiki.archlinux.org/index.php/DisplayLink#USB_3.0_DL-...
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#157Earlier quoted context omitted.
u can use virtual environments for that
In the case of 'Python Virtual Environments' you'd still have to install another version of Python which is non-trivial with Debian based systems without causing some sort of collision, unless you download the binaries to /usr/ or other bin location as suggested.
It provides any version of Python, regardless of what your base system has (or lacks). It also provides an isolated gcc and many other packages; and you can still "pip install" inside it if the package you need is not conda-native, and conda will track it just as well.
Conda is really underappreciated.
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#158I have a Jetson nano. It's a nice thing for what it is, and the price. But, the software misses the mark by a lot. It's still based on Ubuntu 18.04. Want python later than 3.6? Not in the box. A lot of python modules need compiling, and the cpu is what you'd expect. Good for what it is, bad for compiling large numbers or packages. They run a fancy modern desktop based on the Ubuntu one. Sure, it's Nvidia, gotta be fl…
I'm not going to lie, I don't understand the usage of Python and other such languages in the embedded space in general.
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#159Earlier quoted context omitted.
> Want python later than 3.6? apt-get install python3.7 or apt-get install python3.8
That might theoretically trigger updates of packages on which NVidia stuff depends (through indirection), which will then render your system unusable. You might be lucky, though.
Re: Nvidia announces Jetson Nano 2GB, a single board computer
#160What are the use-cases for a GPU-accelerated single board computer?
HDMI out and boots Linux, so could function as desktop replacement. The demos I've seen it really shines in small robotics. Think AWS Deep Racer League style competitions for K-12 ;)
As someone who has tried to run a desktop environment on various Pi-like devices for years, with every generation being "the one that will replace your PC" I just laugh.
The modern web is nearly unusable with less than 4 GB of RAM and it's really easy to push beyond that. I personally would not recommend that anyone try to use anything with less than 8 GB of RAM as a general purpose desktop computer anymore.
You can do it, sure, but there will be significant compromises and limitations along the way. A secondhand x86 PC with 8+ GB of RAM is almost always a better choice for general purpose desktop use. Leave the "hacker boards" for roles that benefit more from their compact size, low power consumption, and/or specialty I/O capabilities.
I haven't tried the Pi 8GB, that should at least solve the RAM problem, but the lack of native high-speed storage still likely impacts usability. Here's hoping the major Pi-likes follow suit to offer variants with more memory soon.
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And of course as noted by other comments, another major reason to think of these things more as appliances is the generally spotty support for updating kernels and the like that is unfortunately standard in the ARM world. That entire side of the industry is infected with NDA culture and has no interest in curing it.