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USB AD 6810 on Nvidia Jetson Plattform

Hello everyone!

 

I have a Labview application which reads the NI USB AD 6810 card with multiple sensors on a windows machine.

In 6-12 month I need to migrate the whole thing to a smaller plattform, so I thought of the nvidia jetson (nano or tx2) because I have some of them laying around.

 

Has anyone an idea how I can quickly port my application to the Jetpack operation system (based on ubuntu)?

An alternative would be to read the USB AD card with c or c++ (evtually python?) directly on linux, but as far as I have seen, there is no support for ubuntu based OS.

 

Thanks in advance for any help!

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Hello, 

Is the device AD6810 a NI production device (I mean is it a USB or PCI device)?

Do you want to use the same VI files on the Labview installed on the new Jetpack operating system? 

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Hi Tidad,

 

just saw that I mistyped the AD card's name:

It's the NI USB AD 6210: https://www.ni.com/de-de/support/model.usb-6210.html

 

I want to use the sensors connected to it (we currently have 14 sensors) and read the data.

For windows we have written a labview application, but the idea is to port it to linux. Eventually grab the data via c/c++/python on linux if that's the easier way.

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Hi, 

Indeed writing the programs again could be time-consuming. Before doing so you might check the compatibility of the new OS with Labview. 
Labview is supported on some Linux OS Distributions you could check the compatibility. Labview.jpg

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Thanks for your answers. I think I will go another way with another AD card.

This thread could be closed.

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Your NVidia Jetson platform is an ARM Cortex®-A CPU. LabVIEW for Linux is compiled for the Intel x64 platform and can not run on this CPU. (Well it theoretically could if Linux had a working Rosetta 2 implementation like Apple has for their new M1 Macs. LabVIEW 2020 SP1 reportedly can be installed on M1 Macs and runs reasonably well, but I doubt Linux will ever have such a seamless x64 emulator for ARM).

 

It could be theoretically targeted with the same system that is used in the Linx Toolkit for Raspberry Pi and Beaglebone Black, but that is absolutely non-trivial to do. I don't see anyone outside of NI R&D having the knowledge and means to do this in a good manner.

Rolf Kalbermatter
My Blog
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