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Miner graphics card tensorflow

Publish: 2021-05-15 17:57:42
1.

bus line: Metro Line 1 → Metro Line 7, the whole journey is about 8.1km

1. Walk about 520 meters from Shanghai to people's Square Station

2. Take Metro Line 1, pass 3 stops, reach Changshu Road Station

3. Walk about 310 meters, transfer to Metro Line 7

4. Take Metro Line 7, pass 2 stops, reach Dong'an Road Station

5. Walk about 810 meters, Arrive at Shanghai Mental Health Center

2.

Check whether the local GPU supports the installation of tensorflow GPU
CUDA and cudnn are required to install the GPU version of tensorflow
therefore, it is necessary to check whether CUDA supports native GPU, and the computing power should be greater than 3.1
according to the official data provided by NVIDIA, gf920m has the computing power of 3.5, which just meets the requirements, and can be installed with GPU version
the specific parameters are shown in the figure below

3. Need to buy external graphics card adapter card! Can install external graphics card, any graphics card can be
4. This is a professional graphics card. Some of you don't support it. This kind of machine is not cheap. If you don't support it, you can't help it. It's not that the more expensive the graphics card, the better. It's what you need.
5. Unknown_Error
6. Deep learning tensorflow - GPU software, this gtx1660ti graphics card can certainly support. I don't know if you have high requirements for deep learning. If you have high requirements, buy an independent graphics card for professional deep learning. If you don't have high requirements, gtx1660ti can also be used and supported,
7. Advanced graphics card can be, if there is a driver problem, please consult and pay attention to download driver
8. Generally speaking, he can only use two at most, so in this respect, we must pay attention not to use too much.
9. Theoretically, it can
although I haven't tried gtx1660ti, there is no problem with gtx1060. There is no reason why the new graphics card doesn't support it. If the owner tests and the acceleration environment doesn't support it, you can replace other compiler versions or refer to the online deep learning environment for reference.
10. Yes, we have to use NVIDIA's,
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