Situation: I currently have a 13 year old workstation I built running Ubuntu 18.04 that runs well, so I don't want replace the motherboard or any other parts until they malfunction. The GPU on this computer is too old to run deep learning tasks with Webots simulations using CUDA.
Solutions 1: Build a new workstation with adequate GPU(s) where I can use the same monitors, keyboard & mouse for both computer via KVM switch. (This I know how to do)
Solution 2: Build a server with adequate GPU(s)
The problem is I don't know if I can use the server to graphically display a Webots simulation of a continuous deep learning training run on the workstation; this is the main thing I'd use the GPU server for. Is this doable? (This is the main important point)
Additionally, would I be able to access the server via ssh over wifi?
It seems needing, over time, to build workstation after workstation may not be as wise as continually modifying a single server?! Is this true?
Solutions 1: Build a new workstation with adequate GPU(s) where I can use the same monitors, keyboard & mouse for both computer via KVM switch. (This I know how to do)
Solution 2: Build a server with adequate GPU(s)
The problem is I don't know if I can use the server to graphically display a Webots simulation of a continuous deep learning training run on the workstation; this is the main thing I'd use the GPU server for. Is this doable? (This is the main important point)
Additionally, would I be able to access the server via ssh over wifi?
It seems needing, over time, to build workstation after workstation may not be as wise as continually modifying a single server?! Is this true?
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