oneDAL
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feature: knn kd tree fix for parallel
Description
PR introduces memory optimizations in Knn KD-tree algorithm. Correct reindexing in parallel mode has been added. Queue helper has been updated.
PR completeness and readability
- [x] I have reviewed my changes thoroughly before submitting this pull request.
- [x] I have commented my code, particularly in hard-to-understand areas.
- [x] I have updated the documentation to reflect the changes or created a separate PR with update and provided its number in the description, if necessary.
- [x] Git commit message contains an appropriate signed-off-by string (see CONTRIBUTING.md for details).
- [x] I have added a respective label(s) to PR if I have a permission for that.
- [x] I have resolved any merge conflicts that might occur with the base branch.
Testing
- [x] I have run it locally and tested the changes extensively.
- [x] All CI jobs are green or I have provided justification why they aren't.
- [x] I have extended testing suite if new functionality was introduced in this PR.
Performance
- [x] I have measured performance for affected algorithms using scikit-learn_bench and provided at least summary table with measured data, if performance change is expected.
- [x] I have provided justification why performance has changed or why changes are not expected.
- [x] I have provided justification why quality metrics have changed or why changes are not expected.
- [x] I have extended benchmarking suite and provided corresponding scikit-learn_bench PR if new measurable functionality was introduced in this PR.
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