Jetson Nano BSP

[Alan Cudmore]

Hi all,

On Thu, Feb 23, 2023 at 4:00 PM Karel Gardas <karel at functional.vision>
wrote:

>
> Hi Prakhar,
>
> On 2/23/23 20:23, Prakhar Agrawal wrote:
> > I completely agree with all your points, but my rationale for
> > introducing the jetson nano or jetson AGX orin was because of their GPU
> > power.
>
> it's really nice what Nvidia achieved here, right? Unfortunately this
> GPU potential is fully locked up by binary driver NVidia provides only
> for selected number of platforms --- if not just for the only one:
> Linux. So very questionable how you would unlock that on RTEMS during
> the limited time of GSoC. Just see what Nouveau folks are doing:
> https://nouveau.freedesktop.org/ -- for years and they just barely got
> to 3D acceleration. Just clone their git repo, see number of patches,
> lines of code provided and number of people involved and I think you
> will get an idea how mamooth task this is...
>
> >
> > In the case of large hobby projects or maybe the initial days of a
> > startup(seed ones), a real-time system that can work with boards having
> > good GPU can do wonders.
> > For example, for an autonomous vehicle L2, L3 autonomy can be achieved
> > using a 60W Jetson AGX orin, hence if RTEMS support is added to the
> > board, it might help create an awesome system to handle all the critical
> > time constraints necessary for the vehicle and give it the ability to
> > coordinate a large number of concurrent activities.
>
> If you are interested in machine vision based on AI and robotics, why
> not to look around for more open-source friendly solution? Recently just
> found i.MX 8M Plus and their claimed 2.3 TOPS NPU. Certainly not that
> powerful like NVidia, but NXP is historically more friendly to 3rd party
> OSes. Not sure about NPU, have not had a time to investigate that yet,
> but perhaps you do?
>
> Also, with i.MX 8M Plus you still do have a chance to use AI Vision in
> non-real time manner running on top of Linux and run RTEMS real-time
> tasks on built in Cortex-M7 -- I mean if you decide that this particular
> BSP may be your GSoC. :-)
>
>
> https://www.nxp.com/products/processors-and-microcontrollers/arm-processors/i-mx-applications-processors/i-mx-8-applications-processors/i-mx-8m-plus-arm-cortex-a53-machine-learning-vision-multimedia-and-industrial-iot:IMX8MPLUS
>
> >> Honestly I'd rather see a new BSP for a decent RISC-V board.
> >
> > I was reading about RISC-V and their comparison with ARM SBC and in one
> > blog I read this - "ARM processors have benefited from a lot more
> > research, funding, and development than RISC-V. This means that it can
> > be argued that RISC-V is being left behind"
>
> Do not worry about it. RISC-V is here and will stay. A lot was already
> invested into it and much more will still be...
>
> I'm working on submitting a RISC-V BSP variant for the Kendryte K210 CPU.
It's low cost and has a 1TOPS NPU. I don't think the NPU needs a binary
driver, and it typically is used with FreeRTOS or bare metal.
But I do like the idea of a dual CPU system where a linux/AI processor can
work with a RTOS based MCU for real time tasks.

Supply chain issues aside, I also am interested in the Pine64 0x64 and its
multiple RISC-V CPUs. I also have been watching the VisionFive 2, which has
a quad-core RISC-V CPU. The VisionFive 2 Linux support is still maturing,
but it does have OpenSBI U-boot, so it might be possible to load RTEMS
images over TFTP.
https://www.kickstarter.com/projects/starfive/visionfive-2
https://wiki.pine64.org/wiki/Ox64

For ARM based AI systems, what about the Beaglebone AI?
https://beagleboard.org/AI

But, maybe a GSOC sized project related to AI would be to integrate a
library such as tensorflow lite or TinyMAIX:
https://github.com/sipeed/TinyMaix
https://www.tensorflow.org/lite

They might work with the well supported RTEMS boards like the Beaglebone
black.

Regards,
Alan


> Karel
>
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