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Jetson AGX Xavier

nvidia.com

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Re: Jetson AGX Xavier

#61

Post by pvg »

goldcd wrote: post #60
bitwize wrote: post #27

Earlier quoted context omitted.

Why do humans carry large, energy-hungry brains around as opposed to being simple tools of the Hivemind like their brethren the insects? Making the edges smarter allows them to react and adapt on smaller timescales.

But we've also developed distributed abilities with quite boggling amounts of specialization. If you chucked one random human on a desert island, they'd probably die. Chuck a dozen, they have a better chance of survival. Chuck a thousand, you might have a civilization. Conversely if you say chucked 2 or 100 rabbits on an island - end result is probably going to be an island full of rabbits.

One Italian plumber and a bunch of rabbids, on the other hand...

Re: Jetson AGX Xavier

#62

Post by p1necone »

BillinghamJ wrote: post #58
p1necone wrote: post #57

Earlier quoted context omitted.

> Comedy answer: iPad Pro I mean, the iPad Pro does have a relatively beefy processor. If only you could run arbitrary code on it.

A lot of instruction sets aren't there yet, but https://ish.app is doing a truly incredible job in this regard. Gives you a working Alpine Linux installation which you can download and install packages for normally, all within the bounds of the normal Apple sandbox, with decent enough performance. It doesn't have SSE or MMX yet, so eg Go and Node aren't usable at this point. But a shocking amount actually does work p…

It's pretty atrocious that you have to run an x86 emulator to use your iPad "pro" for this stuff. This project is super cool though.

Re: Jetson AGX Xavier

#63

Post by TaylorAlexander »

epmaybe wrote: post #59
TaylorAlexander wrote: post #39

Earlier quoted context omitted.

You can certainly do this using machine vision cameras. Either USB3, Gig Ethernet, or CSI interface (16cm max run length I believe). I forget how best to attach two displays to the Xavier but that’s seems doable. I got my cameras from e-consystems and they’ve got some USB3 cameras that could do it. At least I’m pretty sure. My USB3 cameras just showed up and I haven’t tried them yet.

I actually have two econ systems cameras that I've been testing on my desktop/laptop, and it does all right but even then struggles at 4k resolutions.

Interesting. I know e-consystems provided their own kernel modules for the Jetson which help with some of the camera streaming, and they provide a special binary of I think guvcview to view live camera output. That is for Xavier though so I don't know if they have something for just a regular computer.

The other thing to look at is using hardware transcoding in an NVIDIA GPU, a raw 4k feed from a 4k camera is huge, but transcoded to h.264 or better h.265 the footage is much more playable from disk in my experience. It may help with live footage. Here are some notes I made when setting up GPU transcoding.

Using xstack filter:

https://trac.ffmpeg.org/wiki/Create%20a%20mosaic%20out%20of%...

Using h265 (required to support the extra resolution of 4x4k) http://ntown.at/knowledgebase/cuda-gpu-accelerated-h264-h265...

https://devblogs.nvidia.com/nvidia-ffmpeg-transcoding-guide/

What is your monitor resolution? If you can't display the full resolution, I've found that using the nvidia encoder hardware to resize each 4k stream to 720p makes transcoding much faster. I've added my video conversion scripts to github so you can see how I've done that. https://github.com/tlalexander/rover_video_scripts

You can also contact e-consystems, as they seem eager to provide application support. Finally feel free to email me to the email in my profile, or better yet create an account and ask the question on my website http://reboot.love so other people can see our conversation and benefit from what we learn.

EDIT: I JUST saw that you meant one local display and one remote display. Sorry busy day. In that case the other poster mentioning gstreamer is spot on, and I believe econsystems has some gstreamer plug ins at least for some cameras, or maybe nvidia does...

Re: Jetson AGX Xavier

#64

Post by fizixer »

my123 wrote: post #29
fizixer wrote: post #14

Inference only. (So this is competing with Google TPUv1; a few years late and way more expensive, but with more memory)

It can do training with its GPU, not the fastest thing in the world though.

So looks like it can do "checkbox training" (add an iota of training capability just so you could check the box labelled "it does training").

Got it.

Re: Jetson AGX Xavier

#65

Post by [deleted] »

king_magic wrote: post #38

My biggest complaint with the Jetson line is it's all ARM. Look, I get it. But the developer experience is horrible. Building Docker containers for ARM devices is a pain. Hell, building anything for a Jetson can be a pain unless it's a pre-packaged NVIDIA thing - really not a fan of building things from source. Add on top of that NVIDIA's very low level documentation for pretty much any tooling they ship, coupled wit…

[deleted]

Re: Jetson AGX Xavier

#66

Post by hthtegr »

choppaface wrote: post #52
king_magic wrote: post #38

My biggest complaint with the Jetson line is it's all ARM. Look, I get it. But the developer experience is horrible. Building Docker containers for ARM devices is a pain. Hell, building anything for a Jetson can be a pain unless it's a pre-packaged NVIDIA thing - really not a fan of building things from source. Add on top of that NVIDIA's very low level documentation for pretty much any tooling they ship, coupled wit…

The dev support is also bottom-of-the-barrel even if you’re a high-margin cloud customer. For a generous upper bound of what Nvidia considers “software support,” look at TensorRT, where a majority of the useful stuff has either been written by third parties or scoped out the hard way by people trying to use it. Nvidia isn’t really a software company, and their core product has a very narrow user interface. These fact…

This is so frustrating to hear.

I have a bin full of ARM single board computers, and while the hardware on all of them is pretty much up to the task, the software support from all the vendors has been terrible. I'm in the process of switching to Nvidia hoping it would be the exception.

If anyone from Nvidia is reading this, please do everything you can to convince the bosses to allocate the resources required to support a linux machine properly. It takes much more than it seems.

These devices are designed to be in production for a long time, so heavy investments now on the software support are going to give value for a long time. Rather than dragging the feet and slowly getting it right over time and devaluing the product in the process.

Fingers crossed!!

Re: Jetson AGX Xavier

#67

Post by p1necone »

p1necone wrote: post #62
BillinghamJ wrote: post #58

Earlier quoted context omitted.

A lot of instruction sets aren't there yet, but https://ish.app is doing a truly incredible job in this regard. Gives you a working Alpine Linux installation which you can download and install packages for normally, all within the bounds of the normal Apple sandbox, with decent enough performance. It doesn't have SSE or MMX yet, so eg Go and Node aren't usable at this point. But a shocking amount actually does work p…

It's pretty atrocious that you have to run an x86 emulator to use your iPad "pro" for this stuff. This project is super cool though.

Actually wouldn't a userspace ARM "emulator" be faster than an x86 one on an ARM device? Or are you so far removed from running actual CPU instructions that it doesn't matter?

Re: Jetson AGX Xavier

#68

Post by axegon_ »

king_magic wrote: post #38

My biggest complaint with the Jetson line is it's all ARM. Look, I get it. But the developer experience is horrible. Building Docker containers for ARM devices is a pain. Hell, building anything for a Jetson can be a pain unless it's a pre-packaged NVIDIA thing - really not a fan of building things from source. Add on top of that NVIDIA's very low level documentation for pretty much any tooling they ship, coupled wit…

Agreed. They need to figure out how to put an x86 chip in there to make them truly useful. Also 700 bucks is a bit steep for a raspberry pi with a low powered gpu, just saying...

Re: Jetson AGX Xavier

#69

Post by sdan »

king_magic wrote: post #38

My biggest complaint with the Jetson line is it's all ARM. Look, I get it. But the developer experience is horrible. Building Docker containers for ARM devices is a pain. Hell, building anything for a Jetson can be a pain unless it's a pre-packaged NVIDIA thing - really not a fan of building things from source. Add on top of that NVIDIA's very low level documentation for pretty much any tooling they ship, coupled wit…

I use a CI system like Buildkite to build on my Raspberry Pis and then consequently deploy them via Docker Swarm. Working well so far.

Although in a similar HN thread a few days ago, people pointed out that docker buildkit does do cross-architecture compilation, which has been slow, but works on anything!

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