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# Setting CUDA Drivers
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# Setting Up CUDA Libraries
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> :warning: Thesis students only have access to `philae.polito.it`, which does not have a GPU installed (see ["Servers Information"](/servers)). So, this page is only for other group members.
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TO DO |
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Different libraries and programs that use NVIDIA GPUs might need different versions of the CUDA libraries. Therefore, our GPU-equipped servers have different CUDA versions installed. For users, this means that, before compiling or installing a program that requires CUDA, you should run a script to setup the environment properly.
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**IMPORTANT:** A typical situation in which you'll have to do this is *before* installing packages such as `tensorflow-gpu` or `torch` using `pip` in your virtual environment.
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