Improve error message when default pool lacks managed allocation support (#1835)

When ManagedMemoryResource() is called without options on a platform
where the default memory pool does not support managed allocations
(e.g. WSL2), the error from cuMemGetMemPool is now caught and
re-raised as a RuntimeError with actionable guidance.

Made-with: Cursor

Author: Andy-Jost

cuda_core/cuda/core/_memory/_managed_memory_resource.pyx

@@ -11,6 +11,7 @@ from cuda.core._utils.cuda_utils cimport (
     HANDLE_RETURN,
     check_or_create_options,
 )
+from cuda.core._utils.cuda_utils import CUDAError
 
 from dataclasses import dataclass
 import threading
@@ -226,12 +227,25 @@ cdef inline _MMR_init(ManagedMemoryResource self, options):
         )
 
         if opts is None:
-            MP_init_current_pool(
-                self,
-                loc_type,
-                loc_id,
-                cydriver.CUmemAllocationType.CU_MEM_ALLOCATION_TYPE_MANAGED,
-            )
+            try:
+                MP_init_current_pool(
+                    self,
+                    loc_type,
+                    loc_id,
+                    cydriver.CUmemAllocationType.CU_MEM_ALLOCATION_TYPE_MANAGED,
+                )
+            except CUDAError as e:
+                if "CUDA_ERROR_NOT_SUPPORTED" in str(e):
+                    from .._device import Device
+                    if not Device().properties.concurrent_managed_access:
+                        raise RuntimeError(
+                            "The default memory pool on this device does not support "
+                            "managed allocations (concurrent managed access is not "
+                            "available). Use "
+                            "ManagedMemoryResource(options=ManagedMemoryResourceOptions(...)) "
+                            "to create a dedicated managed pool."
+                        ) from e
+                raise
         else:
             MP_init_create_pool(
                 self,

cuda_core/cuda/core/_memory/_memory_pool.pyx

@@ -257,7 +257,9 @@ cdef int MP_init_current_pool(
         self._h_pool = create_mempool_handle_ref(pool)
         self._mempool_owned = False
     ELSE:
-        raise RuntimeError("not supported")
+        raise RuntimeError(
+            "Getting the current memory pool requires CUDA 13.0 or later"
+        )
     return 0
 
 

cuda_core/tests/test_managed_memory_warning.py

@@ -44,6 +44,13 @@ def device_without_concurrent_managed_access(init_cuda):
     return device
 
 
+@requires_cuda_13
+def test_default_pool_error_without_concurrent_access(device_without_concurrent_managed_access):
+    """ManagedMemoryResource() raises RuntimeError when the default pool doesn't support managed."""
+    with pytest.raises(RuntimeError, match="does not support managed allocations"):
+        ManagedMemoryResource()
+
+
 @requires_cuda_13
 def test_warning_emitted(device_without_concurrent_managed_access):
     """ManagedMemoryResource emits a warning when concurrent managed access is unsupported."""