Use an increased release threshold for the default async pool when using `DeviceMemoryResource`

[shwina]

As reported in #756 (comment), allocation via DeviceMemoryResource can be very slow when there are no active allocations. This is due to the default pool being configured with a release threshold of 0.

A fix for this could be for DeviceMemoryResource to configure the default pool to have a larger (or maximum) release threshold via cuMemPoolSetAttribute.

[leofang]

We need to upstream this workaround
https://github.com/NVIDIA/cccl/blob/cf69aecbbadcd80a1107b0db41896b9d697301c9/python/cuda_cccl/cuda/cccl/parallel/experimental/_utils/temp_storage_buffer.py#L21-L33
done in cuda-cccl back to cuda-core. This should be done in DeviceMemoryResource as noted. This performance improvement should be release-noted.