cuda.bindings._v2.driver.graph_add_memcpy_node#

cuda.bindings._v2.driver.graph_add_memcpy_node( intptr_t h_graph, dependencies, size_t num_dependencies, copy_params, intptr_t ctx, ) → intptr_t#

Creates a memcpy node and adds it to a graph.

Creates a new memcpy node and adds it to h_graph with num_dependencies dependencies specified via dependencies. It is possible for num_dependencies to be 0, in which case the node will be placed at the root of the graph. dependencies may not have any duplicate entries. A handle to the new node will be returned in ph_graph_node. When the graph is launched, the node will perform the memcpy described by copy_params. See cuMemcpy3D() for a description of the structure and its restrictions. Memcpy nodes have some additional restrictions with regards to managed memory, if the system contains at least one device which has a zero value for the device attribute CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS. If one or more of the operands refer to managed memory, then using the memory type CU_MEMORYTYPE_UNIFIED is disallowed for those operand(s). The managed memory will be treated as residing on either the host or the device, depending on which memory type is specified.

Parameters:

h_graph (intptr_t) – Graph to which to add the node.
dependencies (object) –
Dependencies of the node. It can be:
- an int as the pointer address to the array, or
- a Python sequence of ints (as pointer addresses).
num_dependencies (size_t) – Number of dependencies.
copy_params (intptr_t) – Parameters for the memory copy.
ctx (intptr_t) – Context on which to run the node.

Returns:

Returns newly created node.

Return type:

intptr_t