Comments (3)
Hello @nfurnon, thank you for your interest in our work!
If this is a bug report, please provide minimum viable code to reproduce your issue, otherwise we can not help you.
from codecarbon.
Hi @nfurnon you can specify the GPUs to track.
For CPUs however it is very hard (impossible?) to know which one you're actually assigned.
What is your cluster environment? SLURM?
Any help on that front would be much appreciated, tell us if you'd be keen on contributing to improve codecarbon
to work in your computational environment
from codecarbon.
For future reference: we're looking into leveraging CUDA_VISIBLE_DEVICES
to handle multi-gpu
from codecarbon.
Related Issues (20)
- Outdated link to conda repository HOT 1
- codecarbon not tracking CPU when RAPL data is available HOT 7
- please reopen #500
- request for enhancements HOT 4
- RFE: Add support for OpenTelemetry metrics and tracing HOT 2
- Secure the API and Dashboard HOT 1
- Postgresql: Cleaning duplicate data
- get the particular GPU energy HOT 2
- Add output parameter HOT 2
- Dynamic Energy mix per country HOT 3
- Intel Xeon CPUs energy consumption HOT 30
- Code Carbon Dashboard
- GPU not found error. pynvml.nvml.NVMLError_NotSupported: Not Supported HOT 6
- Explain dashboard usage in README HOT 2
- d
- Accuracy when deployed on Kubernetes HOT 4
- how add new chipset HOT 2
- Nividia TX2 support ? HOT 2
- Pytorch Lightning - high level tracking not working
- Adding and Choosing TDP values HOT 7
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from codecarbon.