[Fix] Disable NCCL graph buffer registration for the TP LM-head all-to-all (pure-DP decode hang under request bursts) (#38936)
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@@ -226,6 +226,34 @@ def handle_data_parallelism(server_args: Any):
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run_post_process_pass(server_args, _tp_lm_head_all_to_all_default)
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run_post_process_pass(server_args, _dp_lm_head_validation)
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if resolving_view(server_args).enable_tp_lm_head_all_to_all:
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_disable_nccl_graph_buffer_registration()
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def _disable_nccl_graph_buffer_registration() -> None:
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"""Keep NCCL from registering the buffers of the graph-captured PyNccl
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all-to-all.
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NCCL_GRAPH_REGISTER (default on) registers the send/recv buffers of every
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collective captured in a CUDA graph for the lifetime of the graph, and
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peers then move data through those registrations directly. The TP LM-head
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all-to-all is captured in the decode graphs on graph-pool temporaries,
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whose addresses the pool also hands to other tensors, and the registered
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exchange does not survive that: under a burst of new requests (DP ranks
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ramping at different rates) one rank finishes its step while the others
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spin in ncclDevKernel_SendRecv forever, and every DP rank hangs.
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Reproduced on tp4/dp4/ep4 and on a multi-node tp16/dp16/ep16 PD decode
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deployment; disabling the registration removes the hang while dedicated
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all-to-all buffers alone do not. Must run before the schedulers create
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their NCCL communicators, which inherit this environment. An explicit
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setting wins.
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"""
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if os.environ.setdefault("NCCL_GRAPH_REGISTER", "0") != "0":
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logger.warning(
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"NCCL_GRAPH_REGISTER=%s was set explicitly; the graph-captured TP "
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"LM-head all-to-all can deadlock with registered buffers.",
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os.environ["NCCL_GRAPH_REGISTER"],
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)
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def handle_dwdp(server_args: Any):
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@@ -3353,5 +3353,59 @@ class TestNoneMeansUnset(CustomTestCase):
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self.assertIsNotNone(server_args.mamba_full_memory_ratio)
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class TestTpLmHeadAllToAllNcclGraphRegister(unittest.TestCase):
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"""The graph-captured TP LM-head all-to-all must not run with NCCL's
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graph buffer registration: registered graph-pool temporaries deadlock the
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exchange under DP-rank ramps."""
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def _resolve(self, **kwargs):
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# The handler reads the DP-adjusted prefill knobs the pipeline would
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# have settled by then; the dummy-model pipeline itself returns early.
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server_args = ServerArgs(
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model_path="dummy",
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enable_dp_attention=True,
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tp_size=2,
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dp_size=2,
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chunked_prefill_size=8192,
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cuda_graph_config=CudaGraphConfig(
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prefill=PhaseConfig(backend=Backend.DISABLED)
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),
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**kwargs,
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)
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parallel_hook.handle_data_parallelism(server_args)
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return server_args
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def test_pure_dp_decode_node_disables_nccl_graph_register(self):
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with patch.dict(os.environ, {}, clear=False):
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os.environ.pop("NCCL_GRAPH_REGISTER", None)
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server_args = self._resolve(disaggregation_mode="decode")
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self.assertTrue(
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resolution_result(server_args, "enable_tp_lm_head_all_to_all")
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)
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self.assertEqual(os.environ.get("NCCL_GRAPH_REGISTER"), "0")
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def test_explicit_nccl_graph_register_is_kept(self):
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with patch.dict(os.environ, {"NCCL_GRAPH_REGISTER": "1"}, clear=False):
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with self.assertLogs(parallel_hook.logger, level="WARNING") as logs:
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self._resolve(disaggregation_mode="decode")
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self.assertEqual(os.environ["NCCL_GRAPH_REGISTER"], "1")
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self.assertIn("NCCL_GRAPH_REGISTER=1", "\n".join(logs.output))
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def test_without_all_to_all_env_is_untouched(self):
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# Unified serving keeps the all-to-all off by default, and a decode
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# node with the DP LM head never takes the all-to-all.
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for kwargs in (
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{},
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{"disaggregation_mode": "decode", "enable_dp_lm_head": True},
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):
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with self.subTest(**kwargs), patch.dict(os.environ, {}, clear=False):
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os.environ.pop("NCCL_GRAPH_REGISTER", None)
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server_args = self._resolve(**kwargs)
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self.assertFalse(
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resolution_result(server_args, "enable_tp_lm_head_all_to_all")
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)
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self.assertNotIn("NCCL_GRAPH_REGISTER", os.environ)
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if __name__ == "__main__":
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unittest.main()
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