tslearn-team / tslearn-team/tslearn
Can we use GPU and PySpark to improve on clustering time for TimeSeriesKMeans.
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Description
Dear Dev Team,
@ecederstrand @rth @rflamary @apachaves @felixdivo
Can we use GPU and PySpark to improve on clustering time for TimeSeriesKMeans. I currently tried using n_jobs for parallel processing in Databricks but the time taken for clustering is same for 8 CPU and 32CPU machine. It clearly doesn't help.
Can you please suggest what can be the best approach to reduce the time matrix.
Thanks,
Ishwar Sukheja
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Research direction
The issue names TimeSeriesKMeans, n_jobs, Databricks, GPU and PySpark, but no repository file or test. Start by locating the TimeSeriesKMeans implementation and examining how n_jobs is handled, then profile clustering before evaluating a GPU or PySpark approach. Done would require a clearly reproducible performance improvement and documented usage.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, spark
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100