GPU sharing about clusterdata HOT 4 CLOSED

Thanks for your interest in our paper!

1. Yes, a basic GPU sharing version, with both time and space multiplexing, is provided regardless of the DL framework. For a controlled, fine-grained sharing, e.g., each job has at most 50% of GPU time running its kernel (Fig. 8 in AntMan), seeking the framework-level support is one of the methods.

2. It is not derived from "pai_job_duration_estimate_100K.csv" but from the original dataset. The In [10] of the jupyter notebook shown in README produces the "w/ GPU sharing" figures. Yes, without sharing means requests between (0, 1) are changed to 1.

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Thanks for the prompt clarification!
The In [10] of the jupyter notebook shown in README gives Task Num requests hourly plot.
For Fig 8, when I used gpu_wrk_util, it gives much lower values.
Should I used plan_gpu, but will not that give GPUs requested?
Which field basically corresponds to #GPUs allocated?

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Regarding the #GPUs allocated, it is suggested to use plan_gpu.

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Thanks!

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