rmm-cu12

import rmm from rmm.mr import PoolMemoryResource, CudaMemoryResource, set_current_device_resource # Create an upstream resource (e.g., CudaMemoryResource) for the pool upstream = CudaMemoryResource() # Create a PoolMemoryResource with an initial size and an optional maximum size initial_pool_size = 128 * 1024 * 1024 # 128 MiB maximum_pool_size = 1024 * 1024 * 1024 # 1 GiB pool_mr = PoolMemoryResource( upstream=upstream, initial_pool_size=initial_pool_size, maximum_pool_size=maximum_pool_size ) # Set the default RMM memory resource for the current device set_current_device_resource(pool_mr) print(f"RMM current device resource: {rmm.mr.get_current_device_resource()}") # Allocate a DeviceBuffer using the default RMM memory resource # This buffer resides on the GPU buffer_size = 64 * 1024 * 1024 # 64 MiB device_buffer = rmm.DeviceBuffer(size=buffer_size) print(f"Successfully allocated rmm.DeviceBuffer of {device_buffer.size / (1024*1024):.2f} MB on GPU.") # Memory is automatically freed when device_buffer goes out of scope or program exits.