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Adding support for CUDA_VISIBLE_DEVICES #567
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Hello @lipengfeizju! Thanks for using In the meantime, in EmissionsTracker(
...
gpu_ids ="0,3,4"
) Is this what you need? |
Thanks! That's exactly what I need. |
Sorry to reopen the issue again, is it possible to measure the power of several specific CPU cores? (Maybe just like we do for the GPU ids) |
Maybe we could initialize For CPU node could you open another issue and provide the codecarbon debug logs ? Because it's not possible yet but maybe we could imagine a way to do it. |
Thanks! |
Description
In our university's cluster, our goal is to measure the energy consumption of a deep learning model. The server uses SLURM system and we only get 1 A100 ( out of 8 GPUs). The GPU power measurement from codecarbon is about all 8 GPUs, instead of the GPU we have been allocated.
Techinically speaking, I guess in line 184 of
codecarbon/core/gpu.py
, it queries all GPUs from nvml instead of focusing on the GPU we are actually using. To get a more accurate measurement, it would be better to only look up the power consumption related toCUDA_VISIBLE_DEVICES
.Similar discussion about this topic can also be found here in pynvml.
So is it possible to add a new feature to support measurements focusing on
CUDA_VISIBLE_DEVICES
? I think this is important for deep learning applications, since the other non-visiable devices are usually unrelated to the power consumption of the DL applications.Thank you again for providing the code base for carbon measurement.
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