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ray-ascend

API Reference

API Reference¶

Last updated: 03/24/2026

HCCLGroup¶

The main class for HCCL collective communication.

Constructor¶

HCCLGroup(world_size: int, rank: int, group_name: str)

Methods¶

Method	Description
`broadcast(tensor, broadcast_options)`	Broadcast tensor from root rank
`allreduce(tensor, allreduce_options)`	All-reduce tensor across group
`allgather(tensor_list, tensor, allgather_options)`	Gather tensors from all ranks
`reduce(tensor, reduce_options)`	Reduce tensor to root rank
`reducescatter(tensor, tensor_list, reducescatter_options)`	Reduce and scatter
`send(tensor, send_options)`	Send tensor to peer
`recv(tensor, recv_options)`	Receive tensor from peer
`barrier(barrier_options)`	Synchronize all ranks
`destroy_group()`	Clean up communicator resources

YRTensorTransport¶

The main class for YuanRong direct tensor transport.

Constructor¶

YRTensorTransport()

Environment Variables¶

Variable	Description
`YR_DS_WORKER_HOST`	Host address of the YR DataSystem worker (required)
`YR_DS_WORKER_PORT`	Port of the YR DataSystem worker (required)

Methods¶

Method	Description
`tensor_transport_backend()`	Returns "YR"
`is_one_sided()`	Returns True (one-sided communication)
`get_ds_client(device_type)`	Get or create the DataSystem client
`actor_has_tensor_transport(actor)`	Check if actor has YR transport available
`extract_tensor_transport_metadata(obj_id, gpu_object)`	Extract metadata for transport
`recv_multiple_tensors(obj_id, tensor_transport_metadata, communicator_metadata)`	Receive tensors
`garbage_collect(obj_id, tensor_transport_meta)`	Clean up resources

Registration¶

Register YR tensor transport with:

from ray.experimental import register_tensor_transport
from ray_ascend.direct_transport import YRTensorTransport

register_tensor_transport("YR", ["npu", "cpu"], YRTensorTransport)