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In Google Collab you can choose your notebook to run on cpu or gpu environment. Now I have a laptop with NVDIA Cuda Compatible GPU 1050, and latest anaconda. How to have similiar feature to the collab one where I can simply make my python to run on GPU?
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A Jupyter-Lab environment uses the NVLink Timeline and GPU Utilization dashboards under the Linux command line so they can be monitored to measure deep-learning executions from multiple GPUs.
Installation: First, make sure that Nvidia drivers are upto date also you can install cudatoolkit explicitly from here. then install Anaconda add anaconda to the environment while installing. After completion of all the installations run the following commands in the command prompt.
I am answering my own question. Easiest way to do is use connect to Local Runtime (https://research.google.com/colaboratory/local-runtimes.html) then select hardware accelerator as GPU as shown in (https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d).
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