Why does evaluator for an inference job consume so much time in the cluster-trace-gpu-v2020?
- Dominant language
- Jupyter Notebook
- Stars
- 2.2k
- Forks
- 482
- PR merge metrics
- No merged PRs in 30d
Description
1.as shown in the picture"evaluator" is for inference job ,and the "runtime" is giant:

2.in the paper(MLaaS in the Wild: Workload Analysis and Scheduling
in Large-Scale Heterogeneous GPU Clusters),Figure 4a,the taskrun time is also begin 10s
inference job such as Image classification do not need 10s, so, there is no any such job in the cluster? and what is the job consume so much time ?
thank you very much!
Contributor guide
No contributing guide indexed for this repository
Research direction
Review the evaluator and runtime fields in cluster-trace-gpu-v2020, then compare their meanings with Figure 4a of the cited paper. Determine what the evaluator represents, why inference runtimes can be long, and whether the dataset contains the questioned jobs; document the explanation.
Written by the indexing model from the issue text.
Assessment
- Domain
- data
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100