Find available CPU for running ray AOI pipeline. #146
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Find available CPU for running ray AOI pipeline. #146
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add method to get network interface
tcnichol
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Note - running this I used the environment from the pixi.toml file environment cuda128. That matched our setup at NCSA. |
changes in concurrency (avoiding backpressured) adding psutil dependency
relativityhd
requested changes
Jul 31, 2025
| @ray.remote | ||
| def init_worker(): | ||
| # Set critical CUDA variables before any imports | ||
| os.environ["CUDA_VISIBLE_DEVICES"] = "0" # Or your device index |
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Same as above, shouldn't this be done automatically?
using same logger not ray wrapper logger
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I added a few new features to the ray AOI pipeline.
Previously there were more CPUs available, but typically only a small number were used when running the pipeline. I added some more code as a first draft to make sure that the pipeline is using the available CPUs. Other changes are needing to check the current network configuration. New method added to utils.cuda