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[BugFix][v0.18.0] Gate recompute/balance/fused_mc2 by PD mode (#8374)

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### What this PR does / why we need it?
- Enforce recompute scheduler only in PD-disaggregated mode.
- Enforce balance scheduling only in PD-mixed mode.
- Enforce fused MC2 only on PD-disaggregated D-side (kv_consumer).
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### Does this PR introduce _any_ user-facing change?
No
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### How was this patch tested?
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---------

Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
This commit is contained in:
wangxiaoteng888
2026-04-18 18:06:42 +08:00
committed by GitHub
parent c995a959e6
commit 363febb6cb
5 changed files with 288 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
docs/source/user_guide/configuration/additional_config.md
View File

@@ -37,7 +37,7 @@ The following table lists additional configuration options available in vLLM Asc
| `enable_shared_expert_dp` | bool | `False` | When the expert is shared in DP, it delivers better performance but consumes more memory. Currently only DeepSeek series models are supported. |
| `multistream_overlap_shared_expert` | bool | `False` | Whether to enable multi-stream shared expert. This option only takes effect on MoE models with shared experts. |
| `multistream_overlap_gate` | bool | `False` | Whether to enable multi-stream overlap gate. This option only takes effect on MoE models with shared experts. |
| `recompute_scheduler_enable` | bool | `False` | Whether to enable recompute scheduler. |
| `recompute_scheduler_enable` | bool | `False` | Whether to enable the recompute scheduler. **Only valid in PD-disaggregated mode** (`kv_role` is `kv_producer` or `kv_consumer`). **Do not enable in PD-mixed mode** (no `kv_transfer_config`, or `kv_role` is `kv_both`); startup will fail with a clear error. |
| `enable_cpu_binding` | bool | `True` | Whether to enable CPU binding. Only takes effect on ARM CPUs; A3 uses the global-slicing CPU allocation strategy and other device types use the topo-affinity CPU allocation strategy. |
| `SLO_limits_for_dynamic_batch` | int | `-1` | SLO limits for dynamic batch. This is new scheduler to support dynamic batch feature |
| `enable_npugraph_ex` | bool | `False` | Whether to enable npugraph_ex graph mode. |

251
tests/ut/test_platform.py
View File

@@ -418,6 +418,257 @@ class TestNPUPlatform(TestBase):
self.assertEqual(vllm_config.cache_config.block_size, 128)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_recompute_scheduler_rejects_pd_mixed_no_kv_transfer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = True
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = None
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with pytest.raises(ValueError, match=r"recompute_scheduler_enable.*PD-disaggregated.*PD-mixed"):
with patch.object(platform.NPUPlatform, "_fix_incompatible_config"):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_recompute_scheduler_rejects_pd_mixed_kv_both(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = True
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_both", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with pytest.raises(ValueError, match=r"recompute_scheduler_enable.*PD-disaggregated.*PD-mixed"):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_balance_scheduler_rejects_pd_disaggregated_kv_producer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_producer", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_BALANCE_SCHEDULING", True, create=True):
with pytest.raises(ValueError, match=r"VLLM_ASCEND_BALANCE_SCHEDULING.*PD-mixed.*PD-disaggregated"):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_balance_scheduler_rejects_pd_disaggregated_kv_consumer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_consumer", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_BALANCE_SCHEDULING", True, create=True):
with pytest.raises(ValueError, match=r"VLLM_ASCEND_BALANCE_SCHEDULING.*PD-mixed.*PD-disaggregated"):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_fused_mc2_rejects_pd_mixed_no_kv_transfer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_ascend_config.enable_mc2_hierarchy_comm = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = None
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2", 1, create=True):
with pytest.raises(ValueError, match=r"VLLM_ASCEND_ENABLE_FUSED_MC2.*kv_role='kv_consumer'.*PD-mixed"):
with patch.object(platform.NPUPlatform, "_fix_incompatible_config"):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_fused_mc2_rejects_pd_mixed_kv_both(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_ascend_config.enable_mc2_hierarchy_comm = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_both", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2", 1, create=True):
with pytest.raises(ValueError, match=r"VLLM_ASCEND_ENABLE_FUSED_MC2.*kv_role='kv_consumer'.*kv_role='kv_both'"):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_fused_mc2_rejects_pd_disaggregated_kv_producer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_ascend_config.enable_mc2_hierarchy_comm = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_producer", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2", 1, create=True):
with pytest.raises(ValueError, match=r"VLLM_ASCEND_ENABLE_FUSED_MC2.*kv_role='kv_consumer'.*kv_role='kv_producer'"):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
@patch("vllm_ascend.quantization.utils.maybe_auto_detect_quantization")
@patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType.A3)
@patch("vllm_ascend.ascend_config.init_ascend_config")
@patch("vllm_ascend.core.recompute_scheduler.RecomputeSchedulerConfig.initialize_from_config")
def test_check_and_update_config_fused_mc2_allows_pd_disaggregated_kv_consumer(
self, mock_init_recompute, mock_init_ascend, mock_soc_version, mock_auto_detect
):
mock_ascend_config = TestNPUPlatform.mock_vllm_ascend_config()
mock_ascend_config.recompute_scheduler_enable = False
mock_ascend_config.enable_mc2_hierarchy_comm = False
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.kv_transfer_config = MagicMock(kv_role="kv_consumer", engine_id="engine0")
vllm_config.parallel_config.decode_context_parallel_size = 1
vllm_config.parallel_config.prefill_context_parallel_size = 1
vllm_config.parallel_config.tensor_parallel_size = 1
vllm_config.scheduler_config = MagicMock()
mock_init_recompute.return_value = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
self.platform = platform.NPUPlatform()
with patch("vllm_ascend.platform.envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2", 1, create=True):
with (
patch.object(platform.NPUPlatform, "_fix_incompatible_config"),
patch.object(platform, "check_kv_extra_config"),
):
self.platform.check_and_update_config(vllm_config)
def test_update_block_size_for_backend_preserves_hybrid_block_size(self):
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.model_config.is_hybrid = True

1
vllm_ascend/ascend_config.py
View File

@@ -86,6 +86,7 @@ class AscendConfig:
)
self.multistream_overlap_shared_expert = additional_config.get("multistream_overlap_shared_expert", False)
self.multistream_overlap_gate = additional_config.get("multistream_overlap_gate", False)
# PD-disaggregated only (kv_producer/kv_consumer); invalid in PD-mixed (kv_both / no kv_transfer_config).
self.recompute_scheduler_enable = additional_config.get("recompute_scheduler_enable", False)
self.enable_cpu_binding = additional_config.get("enable_cpu_binding", True)

8
vllm_ascend/envs.py
View File

@@ -93,7 +93,9 @@ env_variables: dict[str, Callable[[], Any]] = {
"VLLM_ASCEND_ENABLE_CONTEXT_PARALLEL": lambda: bool(int(os.getenv("VLLM_ASCEND_ENABLE_CONTEXT_PARALLEL", "0"))),
# Whether to anbale dynamic EPLB
"DYNAMIC_EPLB": lambda: os.getenv("DYNAMIC_EPLB", "false").lower(),
# Whether to enable fused mc2(`dispatch_gmm_combine_decode`/`dispatch_ffn_combine` operator)
# Whether to enable fused MC2 (`dispatch_gmm_combine_decode` / `dispatch_ffn_combine`).
# Platform validation: only PD-disaggregated **decode** instances (`kv_role='kv_consumer'`).
# Not supported in PD-mixed mode (`kv_both` or no kv_transfer_config) or on prefill nodes (`kv_producer`).
# 0, or not set: default ALLTOALL and MC2 will be used.
# 1: ALLTOALL and MC2 might be replaced by `dispatch_ffn_combine` operator.
# `dispatch_ffn_combine` can be used only for moe layer with W8A8, EP<=32, non-mtp, non-dynamic-eplb.
@@ -101,7 +103,9 @@ env_variables: dict[str, Callable[[], Any]] = {
# `dispatch_gmm_combine_decode` can be used only for **decode node** moe layer
# with W8A8. And MTP layer must be W8A8.
"VLLM_ASCEND_ENABLE_FUSED_MC2": lambda: int(os.getenv("VLLM_ASCEND_ENABLE_FUSED_MC2", "0")),
# Whether to anbale balance scheduling
# Whether to enable balance scheduling in the v1 scheduler.
# Platform validation: only PD-mixed mode (`kv_role='kv_both'` or no kv_transfer_config).
# Not supported in PD-disaggregated mode (`kv_producer` / `kv_consumer` only).
"VLLM_ASCEND_BALANCE_SCHEDULING": lambda: bool(int(os.getenv("VLLM_ASCEND_BALANCE_SCHEDULING", "0"))),
# use fused op transpose_kv_cache_by_block, default is True
"VLLM_ASCEND_FUSION_OP_TRANSPOSE_KV_CACHE_BY_BLOCK": lambda: bool(

29
vllm_ascend/platform.py
View File

@@ -448,7 +448,36 @@ class NPUPlatform(Platform):
if get_ascend_device_type() != AscendDeviceType._310P:
compilation_config.custom_ops = ["all"]
if envs_ascend.VLLM_ASCEND_ENABLE_FUSED_MC2:
kv_transfer_config = vllm_config.kv_transfer_config
kv_role = getattr(kv_transfer_config, "kv_role", None)
if kv_transfer_config is None or kv_role != "kv_consumer":
raise ValueError(
"VLLM_ASCEND_ENABLE_FUSED_MC2 (fused mc2) only supports PD-disaggregated "
"decode nodes (D-side) with kv_role='kv_consumer'. It is not supported "
"in PD-mixed mode (no kv_transfer_config / kv_role='kv_both') nor on "
"prefill nodes (P-side) with kv_role='kv_producer'."
)
if envs_ascend.VLLM_ASCEND_BALANCE_SCHEDULING:
kv_transfer_config = vllm_config.kv_transfer_config
kv_role = getattr(kv_transfer_config, "kv_role", None)
if kv_transfer_config is not None and kv_role != "kv_both":
raise ValueError(
"VLLM_ASCEND_BALANCE_SCHEDULING (balance scheduling) only supports PD-mixed mode "
"(kv_role='kv_both' or no kv_transfer_config), and is not supported in "
"PD-disaggregated mode (kv_role='kv_producer'/'kv_consumer')."
)
if ascend_config.recompute_scheduler_enable:
kv_transfer_config = vllm_config.kv_transfer_config
kv_role = getattr(kv_transfer_config, "kv_role", None)
if kv_transfer_config is None or kv_role == "kv_both":
raise ValueError(
"recompute_scheduler_enable can only be enabled in PD-disaggregated mode "
"(kv_role='kv_producer' or 'kv_consumer'), and is not supported in PD-mixed mode."
)
from vllm_ascend.core.recompute_scheduler import RecomputeSchedulerConfig
recompute_scheduler_config = RecomputeSchedulerConfig.initialize_from_config(vllm_config)