Hi all, On Thu, Feb 23, 2023 at 4:00 PM Karel Gardas <karel@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 > > _______________________________________________ > devel mailing list > devel@rtems.org > http://lists.rtems.org/mailman/listinfo/devel
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