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[0.11.0][BugFix] Improve the performance of prefixcache features #4021

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Merged
merged 4 commits into from
Nov 10, 2025
Merged

[0.11.0][BugFix] Improve the performance of prefixcache features #4021

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d6ba512
dev_bugfix_prefix_cache_pref
underfituu Nov 6, 2025
ba2d09d
fix_stack_bug
underfituu Nov 6, 2025
007c0c2
fix_lint
underfituu Nov 6, 2025
57de640
fix_ut
underfituu Nov 6, 2025
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6 changes: 5 additions & 1 deletion tests/ut/attention/test_mla_v1.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,7 +82,8 @@ def test_ascend_mla_prefill_metadata_with_chunked_context(self):
seq_tot=seq_tot,
max_seq_lens=max_seq_lens,
workspace=workspace,
chunk_seq_lens=chunk_seq_lens)
chunk_seq_lens=chunk_seq_lens,
chunk_seq_lens_npu=chunk_seq_lens)

metadata = AscendMLAPrefillMetadata(
attn_mask=torch.tensor([[1, 0], [1, 1]], dtype=torch.bool),
Expand All @@ -103,6 +104,8 @@ def test_ascend_mla_prefill_metadata_with_chunked_context(self):
self.assertEqual(metadata.chunked_context.max_seq_lens, max_seq_lens)
self.assertIs(metadata.chunked_context.workspace, workspace)
self.assertIs(metadata.chunked_context.chunk_seq_lens, chunk_seq_lens)
self.assertIs(metadata.chunked_context.chunk_seq_lens_npu,
chunk_seq_lens)


class TestAscendMLADecodeMetadata(TestBase):
Expand Down Expand Up @@ -428,6 +431,7 @@ def test_compute_prefill_context(self, mock_ring, mock_load):
chunk_ctx = MagicMock()
chunk_ctx.seq_tot = [8]
chunk_ctx.chunk_seq_lens = [torch.tensor([8])]
chunk_ctx.chunk_seq_lens_npu = [torch.tensor([8])]
chunk_ctx.starts = [torch.tensor([0])]

prefill_meta = MagicMock()
Expand Down
6 changes: 5 additions & 1 deletion tests/ut/torchair/test_torchair_mla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,8 @@ def test_ascend_mla_prefill_metadata_with_chunked_context(self):
seq_tot=seq_tot,
max_seq_lens=max_seq_lens,
workspace=workspace,
chunk_seq_lens=chunk_seq_lens)
chunk_seq_lens=chunk_seq_lens,
chunk_seq_lens_npu=chunk_seq_lens)

metadata = AscendMLATorchairPrefillMetadata(
attn_mask=torch.tensor([[1, 0], [1, 1]], dtype=torch.bool),
Expand All @@ -107,6 +108,8 @@ def test_ascend_mla_prefill_metadata_with_chunked_context(self):
self.assertEqual(metadata.chunked_context.max_seq_lens, max_seq_lens)
self.assertIs(metadata.chunked_context.workspace, workspace)
self.assertIs(metadata.chunked_context.chunk_seq_lens, chunk_seq_lens)
self.assertIs(metadata.chunked_context.chunk_seq_lens_npu,
chunk_seq_lens)


class TestAscendMLATorchairDecodeMetadata(TestBase):
Expand Down Expand Up @@ -661,6 +664,7 @@ def test_compute_prefill_context(self, mock_ring, mock_load):
chunk_ctx = MagicMock()
chunk_ctx.seq_tot = [8]
chunk_ctx.chunk_seq_lens = [torch.tensor([8])]
chunk_ctx.chunk_seq_lens_npu = [torch.tensor([8])]
chunk_ctx.starts = [torch.tensor([0])]

prefill_meta = MagicMock()
Expand Down
14 changes: 10 additions & 4 deletions vllm_ascend/attention/mla_v1.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,7 @@ class ChunkedContextMetadata:
max_seq_lens: list[int]
workspace: torch.Tensor
chunk_seq_lens: torch.Tensor
chunk_seq_lens_npu: torch.Tensor

attn_mask: torch.Tensor
query_lens: torch.Tensor
Expand Down Expand Up @@ -371,6 +372,7 @@ def build(
seq_tot=chunk_seq_lens.sum(dim=1).tolist(),
max_seq_lens=chunk_seq_lens.max(dim=1).values.tolist(),
chunk_seq_lens=chunk_seq_lens,
chunk_seq_lens_npu=chunk_seq_lens.npu(),
workspace=self.chunked_prefill_workspace,
)
prefill_input_positions = input_positions[tokens_start:]
Expand Down Expand Up @@ -766,16 +768,20 @@ def _compute_prefill_context(

iters = len(prefill_metadata.chunked_context.seq_tot)

seq_len1 = torch.tensor(prefill_metadata.query_lens, dtype=torch.int32)
current_seq_len = torch.tensor(prefill_metadata.query_lens,
dtype=torch.int32)
cache_kv_c = kv_c_and_k_pe_cache[0]
cache_k_pe = kv_c_and_k_pe_cache[1]
num_heads = cache_k_pe.size(2)
latent_kv_dim = kv_c_and_k_pe_cache[0].size(-1)
for i in range(iters):
toks = prefill_metadata.chunked_context.seq_tot[i]

seq_len2 = prefill_metadata.chunked_context.chunk_seq_lens[i]
seq_len = torch.stack([seq_len1, seq_len2])
context_seq_len = prefill_metadata.chunked_context.chunk_seq_lens[
i]
context_seq_len_npu = prefill_metadata.chunked_context.chunk_seq_lens_npu[
i]
seq_len = torch.stack([current_seq_len, context_seq_len])
kv_c_normed = torch.empty(toks,
num_heads,
latent_kv_dim,
Expand All @@ -791,7 +797,7 @@ def _compute_prefill_context(
cache_kv_c,
cache_k_pe,
prefill_metadata.block_table,
seq_len2.to(q_nope.device),
context_seq_len_npu,
seq_starts=prefill_metadata.chunked_context.starts[i],
key=kv_c_normed,
value=k_pe,
Expand Down
14 changes: 10 additions & 4 deletions vllm_ascend/torchair/torchair_mla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,7 @@ class TorchairChunkedContextMetadata:
max_seq_lens: list[int]
workspace: torch.Tensor
chunk_seq_lens: torch.Tensor
chunk_seq_lens_npu: torch.Tensor

attn_mask: torch.Tensor
query_lens: torch.Tensor
Expand Down Expand Up @@ -462,6 +463,7 @@ def build(
seq_tot=chunk_seq_lens.sum(dim=1).tolist(),
max_seq_lens=chunk_seq_lens.max(dim=1).values.tolist(),
chunk_seq_lens=chunk_seq_lens,
chunk_seq_lens_npu=chunk_seq_lens.npu(),
workspace=self.chunked_prefill_workspace,
)
prefill_input_positions = input_positions[tokens_start:]
Expand Down Expand Up @@ -777,16 +779,20 @@ def _compute_prefill_context(
q_pe = query[..., self.qk_nope_head_dim:]
q_nope = query[..., :self.qk_nope_head_dim]

seq_len1 = torch.tensor(prefill_metadata.query_lens, dtype=torch.int32)
current_seq_len = torch.tensor(prefill_metadata.query_lens,
dtype=torch.int32)
cache_kv_c = kv_c_and_k_pe_cache[0]
cache_k_pe = kv_c_and_k_pe_cache[1]
num_heads = cache_k_pe.size(2)
latent_kv_dim = kv_c_and_k_pe_cache[0].size(-1)
for i in range(iters):
toks = prefill_metadata.chunked_context.seq_tot[i]

seq_len2 = prefill_metadata.chunked_context.chunk_seq_lens[i]
seq_len = torch.stack([seq_len1, seq_len2])
context_seq_len = prefill_metadata.chunked_context.chunk_seq_lens[
i]
context_seq_len_npu = prefill_metadata.chunked_context.chunk_seq_lens_npu[
i]
seq_len = torch.stack([current_seq_len, context_seq_len])
kv_c_normed = torch.empty(toks,
num_heads,
latent_kv_dim,
Expand All @@ -802,7 +808,7 @@ def _compute_prefill_context(
cache_kv_c,
cache_k_pe,
prefill_metadata.block_table,
seq_len2.to(query.device),
context_seq_len_npu,
seq_starts=prefill_metadata.chunked_context.starts[i],
key=kv_c_normed,
value=k_pe,
Expand Down