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[Fix] Fix flashinfer cpu <-> gpu synchronization (#8340)

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DarkSharpness
2025-08-09 20:11:40 -07:00
committed by GitHub
parent 19bc77f05c
commit 7ba5ad5766
3 changed files with 65 additions and 24 deletions
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65
python/sglang/srt/layers/attention/flashinfer_backend.py
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@@ -66,6 +66,10 @@ class PrefillMetadata:
# Reuse this workspace buffer across all flashinfer wrappers
global_workspace_buffer = None
# Use as a fast path to override the indptr in flashinfer's plan function
# This is used to remove some host-to-device copy overhead.
global_override_indptr_cpu = None
class FlashInferAttnBackend(AttentionBackend):
"""Flashinfer attention kernels."""
@@ -205,6 +209,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_decode.update(
forward_batch.req_pool_indices,
forward_batch.seq_lens,
forward_batch.seq_lens_cpu,
forward_batch.seq_lens_sum,
decode_wrappers=self.decode_wrappers,
encoder_lens=forward_batch.encoder_lens,
@@ -215,6 +220,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
forward_batch.req_pool_indices,
forward_batch.seq_lens,
forward_batch.seq_lens_cpu,
forward_batch.seq_lens_sum,
prefix_lens=None,
prefill_wrappers=self.prefill_wrappers_paged,
@@ -229,6 +235,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
forward_batch.req_pool_indices,
forward_batch.seq_lens,
forward_batch.seq_lens_cpu,
forward_batch.seq_lens_sum,
prefix_lens=None,
prefill_wrappers=self.prefill_wrappers_verify,
@@ -252,6 +259,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
forward_batch.req_pool_indices,
forward_batch.seq_lens,
forward_batch.seq_lens_cpu,
forward_batch.seq_lens_sum,
prefix_lens,
prefill_wrappers=self.prefill_wrappers_paged,
@@ -327,6 +335,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_decode.update(
req_pool_indices,
seq_lens,
seq_lens.cpu(), # may add a little overhead in capture stage
seq_lens_sum,
decode_wrappers=decode_wrappers,
encoder_lens=encoder_lens,
@@ -358,6 +367,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
req_pool_indices,
seq_lens,
seq_lens.cpu(), # may add a little overhead in capture stage
seq_lens_sum,
prefix_lens=None,
prefill_wrappers=prefill_wrappers,
@@ -387,6 +397,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
req_pool_indices,
seq_lens,
seq_lens.cpu(), # may add a little overhead in capture stage
seq_lens_sum,
prefix_lens=None,
prefill_wrappers=prefill_wrappers,
@@ -414,6 +425,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_decode.update(
req_pool_indices[:bs],
seq_lens[:bs],
seq_lens_cpu[:bs] if seq_lens_cpu is not None else None,
seq_lens_sum,
decode_wrappers=self.decode_cuda_graph_metadata[bs],
encoder_lens=encoder_lens[:bs] if encoder_lens is not None else None,
@@ -423,6 +435,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
req_pool_indices[:bs],
seq_lens[:bs],
seq_lens_cpu[:bs] if seq_lens_cpu is not None else None,
seq_lens_sum,
prefix_lens=None,
prefill_wrappers=self.prefill_cuda_graph_metadata[bs],
@@ -434,6 +447,7 @@ class FlashInferAttnBackend(AttentionBackend):
self.indices_updater_prefill.update(
req_pool_indices[:bs],
seq_lens[:bs],
seq_lens_cpu[:bs] if seq_lens_cpu is not None else None,
seq_lens_sum,
prefix_lens=None,
prefill_wrappers=self.prefill_cuda_graph_metadata[bs],
@@ -581,7 +595,7 @@ class FlashInferAttnBackend(AttentionBackend):
class FlashInferIndicesUpdaterDecode:
def __init__(self, model_runner: ModelRunner, attn_backend: AttentionBackend):
def __init__(self, model_runner: ModelRunner, attn_backend: FlashInferAttnBackend):
# Parse Constants
self.num_qo_heads = (
model_runner.model_config.num_attention_heads // get_attention_tp_size()
@@ -614,6 +628,7 @@ class FlashInferIndicesUpdaterDecode:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
decode_wrappers: List[BatchDecodeWithPagedKVCacheWrapper],
encoder_lens: Optional[torch.Tensor],
@@ -626,6 +641,7 @@ class FlashInferIndicesUpdaterDecode:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
decode_wrappers: List[BatchDecodeWithPagedKVCacheWrapper],
encoder_lens: Optional[torch.Tensor],
@@ -640,30 +656,39 @@ class FlashInferIndicesUpdaterDecode:
self.kv_indptr[0],
None,
spec_info,
seq_lens_cpu,
)
def update_sliding_window(
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
decode_wrappers: List[BatchDecodeWithPagedKVCacheWrapper],
encoder_lens: Optional[torch.Tensor],
spec_info: Optional[Union[EagleDraftInput, EagleVerifyInput]],
):
assert self.sliding_window_size is not None
for wrapper_id in range(2):
if wrapper_id == 0:
# Sliding window attention
paged_kernel_lens_tmp = torch.minimum( # TODO: replace this with clamp
seq_lens,
torch.tensor(self.sliding_window_size + 1),
paged_kernel_lens_tmp = torch.clamp(
seq_lens, max=self.sliding_window_size + 1
)
paged_kernel_lens_sum_tmp = paged_kernel_lens_tmp.sum().item()
if seq_lens_cpu is not None:
seq_lens_cpu_tmp = torch.clamp(
seq_lens_cpu, max=self.sliding_window_size + 1
)
paged_kernel_lens_sum_tmp = seq_lens_cpu_tmp.sum().item()
else:
paged_kernel_lens_sum_tmp = paged_kernel_lens_tmp.sum().item()
kv_start_idx_tmp = seq_lens - paged_kernel_lens_tmp
else:
# Full attention
paged_kernel_lens_tmp = seq_lens
paged_kernel_lens_sum_tmp = seq_lens_sum
seq_lens_cpu_tmp = seq_lens_cpu
kv_start_idx_tmp = None
use_sliding_window_kv_pool = wrapper_id == 0 and isinstance(
@@ -678,6 +703,7 @@ class FlashInferIndicesUpdaterDecode:
self.kv_indptr[wrapper_id],
kv_start_idx_tmp,
spec_info,
seq_lens_cpu=seq_lens_cpu_tmp,
use_sliding_window_kv_pool=use_sliding_window_kv_pool,
)
@@ -685,6 +711,7 @@ class FlashInferIndicesUpdaterDecode:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
decode_wrappers: List[BatchDecodeWithPagedKVCacheWrapper],
encoder_lens: Optional[torch.Tensor],
@@ -709,6 +736,7 @@ class FlashInferIndicesUpdaterDecode:
self.kv_indptr[wrapper_id],
kv_start_idx,
spec_info,
seq_lens_cpu=seq_lens_cpu,
)
def call_begin_forward(
@@ -720,6 +748,7 @@ class FlashInferIndicesUpdaterDecode:
kv_indptr: torch.Tensor,
kv_start_idx: torch.Tensor,
spec_info: Optional[Union[EagleDraftInput, EagleVerifyInput]],
seq_lens_cpu: Optional[torch.Tensor],
use_sliding_window_kv_pool: bool = False,
):
if spec_info is None:
@@ -756,6 +785,14 @@ class FlashInferIndicesUpdaterDecode:
)
)
global global_override_indptr_cpu
locally_override = False
if seq_lens_cpu is not None and global_override_indptr_cpu is None:
locally_override = True
global_override_indptr_cpu = torch.empty_like(kv_indptr, device="cpu")
global_override_indptr_cpu[0] = 0
global_override_indptr_cpu[1 : bs + 1] = torch.cumsum(seq_lens_cpu, dim=0)
wrapper.begin_forward(
kv_indptr,
kv_indices,
@@ -769,9 +806,12 @@ class FlashInferIndicesUpdaterDecode:
non_blocking=True,
)
if locally_override:
global_override_indptr_cpu = None
class FlashInferIndicesUpdaterPrefill:
def __init__(self, model_runner: ModelRunner, attn_backend: AttentionBackend):
def __init__(self, model_runner: ModelRunner, attn_backend: FlashInferAttnBackend):
# Parse Constants
self.num_qo_heads = (
model_runner.model_config.num_attention_heads // get_attention_tp_size()
@@ -806,6 +846,7 @@ class FlashInferIndicesUpdaterPrefill:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
prefix_lens: torch.Tensor,
prefill_wrappers: List[BatchPrefillWithPagedKVCacheWrapper],
@@ -820,6 +861,7 @@ class FlashInferIndicesUpdaterPrefill:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
prefix_lens: torch.Tensor,
prefill_wrappers: List[BatchPrefillWithPagedKVCacheWrapper],
@@ -853,6 +895,7 @@ class FlashInferIndicesUpdaterPrefill:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
prefix_lens: torch.Tensor,
prefill_wrappers: List[BatchPrefillWithPagedKVCacheWrapper],
@@ -898,6 +941,7 @@ class FlashInferIndicesUpdaterPrefill:
self,
req_pool_indices: torch.Tensor,
seq_lens: torch.Tensor,
seq_lens_cpu: Optional[torch.Tensor],
seq_lens_sum: int,
prefix_lens: torch.Tensor,
prefill_wrappers: List[BatchPrefillWithPagedKVCacheWrapper],
@@ -1020,11 +1064,6 @@ class FlashInferIndicesUpdaterPrefill:
)
# Use as a fast path to override the indptr in flashinfer's plan function
# This is used to remove some host-to-device copy overhead.
global global_override_indptr_cpu
class FlashInferMultiStepDraftBackend:
"""
Wrap multiple flashinfer attention backends as one for multiple consecutive
@@ -1056,7 +1095,7 @@ class FlashInferMultiStepDraftBackend:
self.kv_last_page_len = torch.ones(
(max_bs,), dtype=torch.int32, device=model_runner.device
)
self.attn_backends = []
self.attn_backends: List[FlashInferAttnBackend] = []
for i in range(self.speculative_num_steps):
self.attn_backends.append(
FlashInferAttnBackend(
@@ -1176,7 +1215,7 @@ class FlashInferMultiStepDraftBackend:
encoder_lens=None,
forward_mode=ForwardMode.DECODE,
spec_info=forward_batch.spec_info,
seq_lens_cpu=None,
seq_lens_cpu=forward_batch.seq_lens_cpu,
)
self.common_template(forward_batch, self.cuda_graph_kv_indices, call_fn)

20
python/sglang/srt/managers/schedule_batch.py
View File

@@ -1714,16 +1714,16 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
attention_backend_str = global_server_args_dict["prefill_attention_backend"]
# Create seq_lens_cpu when needed
if (
attention_backend_str == "fa3"
or (
global_server_args_dict["use_mla_backend"]
and attention_backend_str == "flashinfer"
)
or attention_backend_str == "flashmla"
or attention_backend_str == "cutlass_mla"
or attention_backend_str == "ascend"
or attention_backend_str == "trtllm_mha"
or attention_backend_str == "aiter"
attention_backend_str
in [
"fa3",
"flashinfer",
"flashmla",
"cutlass_mla",
"ascend",
"trtllm_mha",
"aiter",
]
or global_server_args_dict["enable_two_batch_overlap"]
):
seq_lens_cpu = (

4
python/sglang/srt/model_executor/cuda_graph_runner.py
View File

@@ -729,10 +729,12 @@ class CudaGraphRunner:
self.out_cache_loc[:raw_num_token].copy_(forward_batch.out_cache_loc)
self.positions[:raw_num_token].copy_(forward_batch.positions)
seq_lens_cpu = None
if forward_batch.seq_lens_cpu is not None:
if bs != raw_bs:
self.seq_lens_cpu.fill_(self.seq_len_fill_value)
self.seq_lens_cpu[:raw_bs].copy_(forward_batch.seq_lens_cpu)
seq_lens_cpu = self.seq_lens_cpu[:bs]
if pp_proxy_tensors:
for key in self.pp_proxy_tensors.keys():
@@ -766,7 +768,7 @@ class CudaGraphRunner:
self.encoder_lens[:bs] if self.is_encoder_decoder else None,
self.capture_forward_mode,
forward_batch.spec_info,
seq_lens_cpu=self.seq_lens_cpu[:bs],
seq_lens_cpu=seq_lens_cpu,
)
# Store fields