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[NIXL] use Host buffer to support TP_ratio > 1 for XPU (#27140)

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Signed-off-by: Chendi Xue <chendi.xue@intel.com>
Signed-off-by: Chendi.Xue <chendi.xue@intel.com>
Co-authored-by: Nicolò Lucchesi <nicolo.lucchesi@gmail.com>
This commit is contained in:
Chendi.Xue
2025-10-22 10:28:13 -05:00
committed by GitHub
parent 9771e0b432
commit 7c4767f1eb
2 changed files with 34 additions and 5 deletions
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29
vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
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@@ -755,6 +755,7 @@ class NixlConnectorWorker:
self._use_flashinfer = attn_backend == _Backend.FLASHINFER
self._use_pallas = attn_backend == _Backend.PALLAS
self.kv_cache_layout = get_kv_cache_layout()
self.host_buffer_kv_cache_layout = self.kv_cache_layout
logger.debug("Detected attention backend %s", self.backend_name)
logger.debug("Detected kv cache layout %s", self.kv_cache_layout)
@@ -875,6 +876,20 @@ class NixlConnectorWorker:
for layer_name, kv_cache in kv_caches.items():
kv_shape = kv_cache.shape
kv_dtype = kv_cache.dtype
if (
self.kv_cache_layout == "NHD"
and self.vllm_config.kv_transfer_config is not None
and self.vllm_config.kv_transfer_config.enable_permute_local_kv
):
logger.info_once(
"'enable_permute_local_kv' flag is enabled while "
"device KV Layout is NHD. Init host buffer with"
" HND to better support Decode/Prefill TP_ratio > 1."
)
# Since NHD will not support Decode/Prefill TP_ratio > 1,
# we can leverage host_buffer for permute
self.host_buffer_kv_cache_layout = "HND"
kv_shape = tuple(kv_shape[i] for i in [0, 1, 3, 2, 4])
xfer_buffers[layer_name] = torch.empty(
kv_shape, dtype=kv_dtype, device="cpu"
)
@@ -1110,7 +1125,9 @@ class NixlConnectorWorker:
num_blocks=self.num_blocks,
block_lens=self.block_len_per_layer,
attn_backend_name=self.backend_name,
kv_cache_layout=self.kv_cache_layout,
kv_cache_layout=self.kv_cache_layout
if not self.use_host_buffer
else self.host_buffer_kv_cache_layout,
)
ready_event, stop_event = threading.Event(), threading.Event()
self._nixl_handshake_listener_t = threading.Thread(
@@ -1273,7 +1290,12 @@ class NixlConnectorWorker:
assert not self._use_pallas or tp_ratio == 1, (
"TPU (pallas_v1) DOES NOT support heterogeneous TP yet."
)
if not self.use_mla and nixl_agent_meta.kv_cache_layout != self.kv_cache_layout:
kv_cache_layout = (
self.kv_cache_layout
if not self.use_host_buffer
else self.host_buffer_kv_cache_layout
)
if not self.use_mla and nixl_agent_meta.kv_cache_layout != kv_cache_layout:
if (
self.kv_transfer_config.enable_permute_local_kv
and nixl_agent_meta.kv_cache_layout == "HND"
@@ -1299,9 +1321,6 @@ class NixlConnectorWorker:
)
remote_block_size = remote_block_len // (self.slot_size_per_layer[0])
else:
if tp_ratio > 1 and self.device_type == "xpu":
# XPU uses NHD, hence it does not support splitting on H
raise ValueError("Heterogeneous TP is not supported on XPU")
# When MLA is not used, this is a list of the same block length
for block_len in nixl_agent_meta.block_lens:
assert block_len == remote_block_len, (