You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
Repository navigation
Use an increased release threshold for the default async pool when using DeviceMemoryResource #771
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.
Activity
leofang commentedon Aug 21, 2025
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.