New perf. metrics, stability and other improvements

[Alexsandruss]

Description

Changes:

• Add support of LightGBM daal4py modelbuilders
• Add garbage collection and result cleaning in datasets prefetching function to avoid out-of-memory errors
• Add SKLBENCH_DATA_CACHE env variable as the first default location for datasets cache for convenience ($PWD/data_cache is still working if env variable is not set)
• Change default dtype to float32
• Adjust compatibility mode of report generator to work with latest versions of stock sklearn and RAPIDS and for other cases
• Update collected performance metrics:
  • Add cost metrics counted in microdollars (most readable degree for usual case computation time)
  • Add CPU load profiling
  • Add RAM and VRAM usage profiling
  • Add coefficient of variation for time
  • Add 1st run time
  • Add 1st-mean run ratio
• Change color scale from RED-YELLOW-GREEN to RED-WHITE-GREEN in perf. report for better readability
• Add option for cache flushing between case runs
• Docs:
  • Mention Kaggle dataset download requirements
  • Note about experimental configs content and meaning
  • Move Benchmarking Config Specification to separate file
  • Add benchmarking scopes short explanation

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• I have reviewed my changes thoroughly before submitting this pull request.
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