release 24.08 [skip ci]

[YanxuanLiu]

Merge to main for 24.08 release

Release notes as follows:

• Removed MAXINT limit on number of non-zero inputs per GPU for sparse logistic regression.
• IVF-PQ and Cagra were added to the suite of supported approximate nearest neighbor algorithms.
• Extended benchmarking scripts to be compatible with Databricks runtime 13.3 with the spark-rapids plugin and 14.3 and 15.4 without the plugin.
• Included an experimental CLI for no-import-statement-change acceleration of pyspark.ml applications.
• Fixed a slow down for inputs having a large number of columns when type conversion is required.
• Updated RAPIDS dependencies to 24.08.
• Known issues to be fixed in next release:
  • for sparse logistic regression fit a low-level C++/CUDA exception is raised if a partition has no non-zero data.
  • array type inputs with int dtypes are not converted to float leading to errors in some algorithms (e.g. cagra ann)
  • in ivf-pq based Cagra the intermediate graph degree must <= 128 or a low-level C++ exception is raised
  • test_sparse_int64 test requires 256GB host memory to run and not 128GB stated in the comments

NOTE: this PR must be merged as create a merge commit

[YanxuanLiu]

@eordentlich Please help to add release note, thanks!

[YanxuanLiu]

build