CODEWITHSUNDEEP
google-cloud-platformgpugoogle-colaboratory
Brian Barry
Brian Barry

Reputation: 559

Why isn't my colab notebook using the GPU?

When I run code on my colab notebook after having selected the GPU, I get a message saying "You are connected to a GPU runtime, but not utilizing the GPU". Now I understand similar questions have been asked before, but I still don't understand why. I am running PCA on a dataset over hundreds of iterations, for multiple trials. Without a GPU it takes about as long as it does on my laptop, which can be >12 hours, resulting in a time out on colab. Is colab's GPU restricted to machine learning libraries like tensorflow only? Is there a way around this so I can take advantage of the GPU to speed up my analysis?

Upvotes: 1

Views: 3699

Answers (1)

Ismail
Ismail

Reputation: 1078

Colab is not restricted to Tensorflow only.

Colab offers three kinds of runtimes: a standard runtime (with a CPU), a GPU runtime (which includes a GPU) and a TPU runtime (which includes a TPU).

"You are connected to a GPU runtime, but not utilizing the GPU" indicates that the user is conneted to a GPU runtime, but not utilizing the GPU, and so a less costly CPU runtime would be more suitable.

Therefore, you have to use a package that utilizes the GPU, such as Tensorflow or Jax. GPU runtimes also have a CPU, and unless you are specifically using packages that exercise the GPU, it will sit idle.

Upvotes: 2

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