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Adjust rmm pool handling in PDSH benchmarks (#20138)
This updates the handling of the RMM Pool argument for the PDSH CLI. Previously, `--rmm-pool-size` was used for both sync and async RMM memory resources.
As described in rapidsai/rmm#2060, the meaning of the pool size is different for these two types of memory resources, and rapidsai/dask-cuda#1563 is deprecating passing a pool size to `dask_cuda.LocalCUDACluster` with `rmm_async=True`.
No real difference in the timings (maybe a small improvement, but more likely just noise):
```
# New default
python python/cudf_polars/cudf_polars/experimental/benchmarks/pdsh.py --path /datasets/toaugspurger/tpch/scale-100/ --no-print-results --executor streaming --scheduler distributed --iterations 3 --rmm-async 1,2,3,4,5
# Total mean time across all queries: 45.6239 seconds
# Previous default
python python/cudf_polars/cudf_polars/experimental/benchmarks/pdsh.py --path /datasets/toaugspurger/tpch/scale-100/ --no-print-results --executor streaming --scheduler distributed --iterations 3 --rmm-async --rmm-pool-size 0.5 1,2,3,4,5
# Total mean time across all queries: 47.8799 seconds
```
Authors:
- Tom Augspurger (https://github.com/TomAugspurger)
Approvers:
- Richard (Rick) Zamora (https://github.com/rjzamora)
- Bradley Dice (https://github.com/bdice)
URL: #20138
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