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change mla itf into persistent version #626

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Merged
Zzz9990 merged 3 commits into from
Aug 8, 2025
Merged

change mla itf into persistent version #626

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3c7b034
change mla itf into persistent version
Zzz9990 Aug 7, 2025
6e2d818
update vllm
Zzz9990 Aug 8, 2025
ef23553
Merge branch 'deepseek_085' into deepseek_085_mla_persistent
Zzz9990 Aug 8, 2025
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74 changes: 51 additions & 23 deletions vllm/attention/ops/rocm_aiter_mla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,11 +39,17 @@ def aiter_mla_decode_fwd(
logit_cap=0.0,
num_kv_splits=None,
num_kv_splits_indptr=None,
batch_split_table=None,
split_table=None,
splits=None,
q_rope=None,
k_rope=None,
work_indptr=None,
work_info_set=None,
reduce_indptr=None,
reduce_final_map=None,
reduce_partial_map=None,

# batch_split_table=None,
# split_table=None,
# splits=None,
# q_rope=None,
# k_rope=None,
):
torch.ops.vllm.rocm_aiter_mla_decode_fwd(
q,
Expand All @@ -59,11 +65,16 @@ def aiter_mla_decode_fwd(
logit_cap,
num_kv_splits,
num_kv_splits_indptr,
batch_split_table,
split_table,
splits,
q_rope,
k_rope,
work_indptr,
work_info_set,
reduce_indptr,
reduce_final_map,
reduce_partial_map,
# batch_split_table,
# split_table,
# splits,
# q_rope,
# k_rope,
)


Expand All @@ -81,11 +92,17 @@ def mla_decode_fwd_impl(
logit_cap: Optional[float] = 0.0,
num_kv_splits: Optional[int] = 1,
num_kv_splits_indptr: Optional[torch.Tensor] = None,
batch_split_table: Optional[torch.Tensor] = None,
split_table: Optional[torch.Tensor] = None,
splits: Optional[torch.Tensor] = None,
q_rope: Optional[torch.Tensor] = None,
k_rope: Optional[torch.Tensor] = None,
work_indptr: Optional[torch.Tensor] = None,
work_info_set: Optional[torch.Tensor] = None,
reduce_indptr: Optional[torch.Tensor] = None,
reduce_final_map: Optional[torch.Tensor] = None,
reduce_partial_map: Optional[torch.Tensor] = None,

# batch_split_table: Optional[torch.Tensor] = None,
# split_table: Optional[torch.Tensor] = None,
# splits: Optional[torch.Tensor] = None,
# q_rope: Optional[torch.Tensor] = None,
# k_rope: Optional[torch.Tensor] = None,
) -> None:
from aiter.mla import mla_decode_fwd_dispatch

Expand All @@ -101,9 +118,14 @@ def mla_decode_fwd_impl(
logit_cap=logit_cap,
num_kv_splits=num_kv_splits,
num_kv_splits_indptr=num_kv_splits_indptr,
batch_split_table=batch_split_table,
split_table=split_table,
cu_num=splits,
work_indptr=work_indptr,
work_info_set=work_info_set,
reduce_indptr=reduce_indptr,
reduce_final_map=reduce_final_map,
reduce_partial_map=reduce_partial_map,
# batch_split_table=batch_split_table,
# split_table=split_table,
# cu_num=splits,
)


Expand All @@ -121,11 +143,17 @@ def mla_decode_fwd_fake(
logit_cap: Optional[float] = 0.0,
num_kv_splits: Optional[int] = 1,
num_kv_splits_indptr: Optional[torch.Tensor] = None,
batch_split_table: Optional[torch.Tensor] = None,
split_table: Optional[torch.Tensor] = None,
splits: Optional[torch.Tensor] = None,
q_rope: Optional[torch.Tensor] = None,
k_rope: Optional[torch.Tensor] = None,
work_indptr: Optional[torch.Tensor] = None,
work_info_set: Optional[torch.Tensor] = None,
reduce_indptr: Optional[torch.Tensor] = None,
reduce_final_map: Optional[torch.Tensor] = None,
reduce_partial_map: Optional[torch.Tensor] = None,

# batch_split_table: Optional[torch.Tensor] = None,
# split_table: Optional[torch.Tensor] = None,
# splits: Optional[torch.Tensor] = None,
# q_rope: Optional[torch.Tensor] = None,
# k_rope: Optional[torch.Tensor] = None,
) -> None:
pass

Expand Down
65 changes: 47 additions & 18 deletions vllm/v1/attention/backends/mla/rocm_aiter_mla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,11 @@ class AiterMLADecodeMetadata(MLACommonDecodeMetadata):
batch_split_table: Optional[torch.Tensor] = None
split_table: Optional[torch.Tensor] = None
splits: Optional[torch.Tensor] = None
work_indptr: Optional[torch.Tensor] = None
work_info_set: Optional[torch.Tensor] = None
reduce_indptr: Optional[torch.Tensor] = None
reduce_final_map: Optional[torch.Tensor] = None
reduce_partial_map: Optional[torch.Tensor] = None


class AiterMLAMetadata(MLACommonMetadata[AiterMLADecodeMetadata]):
Expand Down Expand Up @@ -150,31 +155,48 @@ def _build_decode(self, input_positions: torch.Tensor,
qo_indptr,
) = self._get_paged_kv_tensors(block_table, seq_lens)

num_kv_splits_indptr = torch.empty(200, dtype=torch.int32, device=block_table.device)
batch_split_table = torch.empty(480, dtype=torch.int32, device=block_table.device)
split_table = torch.empty(480, dtype=torch.int32, device=block_table.device)
splits = torch.empty(1, dtype=torch.int32, device=block_table.device)
# num_kv_splits_indptr = torch.empty(200, dtype=torch.int32, device=block_table.device)
# batch_split_table = torch.empty(480, dtype=torch.int32, device=block_table.device)
# split_table = torch.empty(480, dtype=torch.int32, device=block_table.device)
# splits = torch.empty(1, dtype=torch.int32, device=block_table.device)

import aiter
max_seqlen_qo = 1
num_kv_splits_indptr = None
# work_indptr = None
# work_info_set = None
# reduce_indptr = None
# reduce_final_map = None
# reduce_partial_map = None

work_indptr = torch.empty([81], dtype=torch.int32, device="cuda")
work_info_set = torch.empty([batch_size + 80, 8], dtype=torch.int32, device="cuda")
reduce_indptr = torch.empty([batch_size + 1], dtype=torch.int32, device="cuda")
reduce_final_map = torch.empty([batch_size, 2], dtype=torch.int32, device="cuda")
reduce_partial_map = torch.empty([batch_size], dtype=torch.int32, device="cuda")

if max_seqlen_qo == 1 or paged_kv_indptr[-1] < 16 * 128:
num_kv_splits_indptr = None
batch_split_table = None
split_table = None
splits = None
else:
aiter.get_mla_metadata_impl(paged_kv_indptr, num_kv_splits_indptr, batch_split_table, split_table, splits)
# aiter.get_mla_metadata_impl(paged_kv_indptr, num_kv_splits_indptr, batch_split_table, split_table, splits)
# if get gpu hang, please use cpu metadata as following:
# num_kv_splits_indptr = torch.empty(200, dtype=torch.int32, device=block_table.device)
# kv_seq_les = torch.empty(200, dtype=torch.int32, device=block_table.device)
# aiter.mla.get_meta_param_balanced(paged_kv_indptr, num_kv_splits_indptr, batch_split_table, split_table, kv_seq_les, splits)

# double check
#if num_kv_splits_indptr[0] == -1:
# num_kv_splits_indptr=None
# batch_split_table=None
# split_table=None
aiter.get_mla_metadata_v1(
qo_indptr,
paged_kv_indptr,
16, # nhead // nhead_kv,
1, # nhead_kv,
True,
work_info_set,
work_indptr,
reduce_indptr,
reduce_final_map,
reduce_partial_map,
)

attn_metadata = AiterMLADecodeMetadata(
input_positions=input_positions,
Expand All @@ -184,9 +206,11 @@ def _build_decode(self, input_positions: torch.Tensor,
paged_kv_indices=paged_kv_indices,
paged_kv_last_page_len=paged_last_page_len,
num_kv_splits_indptr=num_kv_splits_indptr,
batch_split_table=batch_split_table,
split_table=split_table,
splits=splits,
work_indptr=work_indptr,
work_info_set=work_info_set,
reduce_indptr=reduce_indptr,
reduce_final_map=reduce_final_map,
reduce_partial_map=reduce_partial_map,
qo_indptr=qo_indptr)

return attn_metadata
Expand Down Expand Up @@ -279,9 +303,14 @@ def _forward_decode(
max_seqlen_qo, self.scale,
True, 0.0, 1,
attn_metadata.decode.num_kv_splits_indptr,
attn_metadata.decode.batch_split_table,
attn_metadata.decode.split_table,
attn_metadata.decode.splits,
attn_metadata.decode.work_indptr,
attn_metadata.decode.work_info_set,
attn_metadata.decode.reduce_indptr,
attn_metadata.decode.reduce_final_map,
attn_metadata.decode.reduce_partial_map,
# attn_metadata.decode.batch_split_table,
# attn_metadata.decode.split_table,
# attn_metadata.decode.splits,
)

return self._v_up_proj_and_o_proj(o)
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