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Nvidia announces Jetson Nano 2GB, a single board computer

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Re: Nvidia announces Jetson Nano 2GB, a single board computer

#3
post #2

tl;dr: It's the same device as before in terms of processing, but with less RAM and fewer connectivity options (and therefore cheaper)

More than that.

They dropped Display Port, the second CSI Camera Connector, the M2 slot, the USB slot and replaced the barrel jack with the USBC.

Thats a decent downgrade of capability

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#4
post #2

tl;dr: It's the same device as before in terms of processing, but with less RAM and fewer connectivity options (and therefore cheaper)

More than that. They dropped Display Port, the second CSI Camera Connector, the M2 slot, the USB slot and replaced the barrel jack with the USBC. Thats a decent downgrade of capability

[deleted]

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#7
post #5

What are the use-cases for a GPU-accelerated single board computer?

Better to understand this as; What is the use-case of RPi combined with machine learning?

More specific; What is the use case of a battery enabled robot “brain” with machine learning?

Re: Nvidia announces Jetson Nano 2GB, a single board computer

#10
post #5

What are the use-cases for a GPU-accelerated single board computer?

Apparently there's a big Software Defined Radio (SDR) community that appreciates the TFlops of floating point compute. cuSignal in particular.

Note that embedded radios / modems / codec manipulation is incredibly common. Usually its handled by a DSP (VLIW architecture), but I'd imagine that the GPU architecture has more FLOPs. DSPs probably have less latency, but something like SDR is not very latency sensitive (or more like: the community models latency as a phase-shift and is therefore resilient to many forms of latency)

Note: I'm not actually in any of these communities. I'm just curious and someone else told me about this very same question.

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