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Is your feature request related to a problem? Please describe.
As a student, GPU allocation has more priority than performance when running the Jupyter Notebook materials that include models such as GAN/Transformer in their lecture. The medium performance GPU is enough but running on CPU causes the delay of progress of the time limited lecture.
Describe the solution you'd like
The students can run GPU instance anytime if they turn on the performance not guarantee GPU checkbox when launching the GPU instance.
Describe alternatives you've considered
The students give up using Studio Lab and select other free notebook service that they can use GPU.
icoxfog417
changed the title
Choose the trade-off of GPU between the performance and allocation
Launching the GPU anytime when checking the performance not guarantee
Apr 1, 2022
icoxfog417
changed the title
Launching the GPU anytime when checking the performance not guarantee
Launching the GPU instance anytime when checking the performance guarantee off
Apr 1, 2022
Is your feature request related to a problem? Please describe.
As a student, GPU allocation has more priority than performance when running the Jupyter Notebook materials that include models such as GAN/Transformer in their lecture. The medium performance GPU is enough but running on CPU causes the delay of progress of the time limited lecture.
Describe the solution you'd like
The students can run GPU instance anytime if they turn on the performance not guarantee GPU checkbox when launching the GPU instance.
Describe alternatives you've considered
The students give up using Studio Lab and select other free notebook service that they can use GPU.
Additional context
This issue is from #92
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