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I am going to buy a laptop to do some TF work. Is the GPU version of TF able to take advantage of Nvidia Quadro P1000 and P2000? Will it run faster on these two GPUs than on the mobile version of 1050Ti? Thanks

lovedrinking
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If I am correct, Tensorflow can run in all Nvidia devices that supports CUDA.

Check this website for their computational compabilities:

https://developer.nvidia.com/cuda-gpus

There you can see the computational power of Nvidia GPU cards.

For your questions about those three cards (P1000, P2000, GeForce 1050Ti), they all have the same computational capabilities: 6.1, which means they won't differ too much in GPU computation.

But from their datasheet (P2000, P1000, 1050ti):

---------------------------------------------------------
|          | Memory | Memory Interface | Memory Bandwidth|
---------------------------------------------------------
|P1000     |4G GDRR5|  128 bit         |     82Gb/s      |
|P2000     |5G GDDR5|  160 bit         |     140Gb/s     |
|1050Ti    |4G GDDR5|  128 bit         |     112Gb/s     |
---------------------------------------------------------

I would say, P2000 > 1050Ti > P1000

BTW, what does that 6.1 number mean? Basically, it means how much operations and functions they can support. You can find the details in the figure below and this link, and similar discussion here

enter image description here

null
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  • Hi ! Could you summarize the infos from the webpage you linked, perhaps with a table comparing the 3 models mentioned in the question? Also, could you provide information about whether or not the devices mentioned in the question are compatible with CUDA? I think it would make this answer more reliable in future use. – Lescurel Aug 14 '18 at 12:12