[FEAT][ROCm] Upgrade AITER MLA v1 backend (#18338)

Signed-off-by: vllmellm <[email protected]>
Co-authored-by: Luka Govedič <[email protected]>

Author: vllmellm

docker/Dockerfile.rocm_base

@@ -12,7 +12,7 @@ ARG PYTORCH_REPO="https://github.com/pytorch/pytorch.git"
 ARG PYTORCH_VISION_REPO="https://github.com/pytorch/vision.git"
 ARG FA_BRANCH="1a7f4dfa"
 ARG FA_REPO="https://github.com/Dao-AILab/flash-attention.git"
-ARG AITER_BRANCH="5a77249"
+ARG AITER_BRANCH="c1debd8"
 ARG AITER_REPO="https://github.com/ROCm/aiter.git"
 
 FROM ${BASE_IMAGE} AS base

vllm/v1/attention/backends/mla/rocm_aiter_mla.py

@@ -53,6 +53,8 @@ class AiterMLADecodeMetadata(MLACommonDecodeMetadata):
     # The number of entries in the last page of each request in
     # the paged kv cache, shape: [batch_size]
     paged_kv_last_page_len: Optional[torch.Tensor] = None
+    # The query indptr, shape : [num_decode + 1]
+    qo_indptr: Optional[torch.Tensor] = None
 
 
 class AiterMLAMetadata(MLACommonMetadata[AiterMLADecodeMetadata]):
@@ -75,27 +77,33 @@ def _get_paged_kv_tensors(
             seq_lens: torch.Tensor) -> tuple[torch.Tensor, ...]:
         page_size = self.runner.block_size
         block_table_bounds = (seq_lens + page_size - 1) // page_size
+        device = self.runner.device
 
         mask = (torch.arange(block_table.size(1),
                              dtype=block_table.dtype,
-                             device=block_table.device).unsqueeze(0)
+                             device=device).unsqueeze(0)
                 < block_table_bounds.unsqueeze(1))
         paged_kv_indices = block_table[mask]
 
         paged_kv_indptr = torch.cat([
-            torch.zeros(1,
-                        dtype=block_table_bounds.dtype,
-                        device=block_table_bounds.device),
+            torch.zeros(1, dtype=block_table_bounds.dtype, device=device),
             block_table_bounds.cumsum(dim=0, dtype=torch.int32)
         ])
 
         paged_kv_last_page_len = seq_lens % page_size
         paged_kv_last_page_len = torch.where(paged_kv_last_page_len == 0,
                                              page_size, paged_kv_last_page_len)
+        qo_indptr = torch.arange(0,
+                                 self._num_decodes + 1,
+                                 step=1,
+                                 dtype=torch.int32,
+                                 device=device)
+
         return (
             paged_kv_indices,
             paged_kv_indptr,
             paged_kv_last_page_len,
+            qo_indptr,
         )
 
     def _build_decode(self, block_table_tensor: torch.Tensor,
@@ -105,14 +113,16 @@ def _build_decode(self, block_table_tensor: torch.Tensor,
             paged_kv_indices,
             paged_kv_indptr,
             paged_last_page_len,
+            qo_indptr,
         ) = self._get_paged_kv_tensors(block_table_tensor, seq_lens)
 
         attn_metadata = AiterMLADecodeMetadata(
             block_table=block_table_tensor,
             seq_lens=seq_lens,
             paged_kv_indptr=paged_kv_indptr,
             paged_kv_indices=paged_kv_indices,
-            paged_kv_last_page_len=paged_last_page_len)
+            paged_kv_last_page_len=paged_last_page_len,
+            qo_indptr=qo_indptr)
 
         return attn_metadata
 
@@ -137,7 +147,10 @@ def __init__(
                          alibi_slopes, sliding_window, kv_cache_dtype,
                          blocksparse_params, logits_soft_cap, attn_type,
                          **mla_args)
-
+        assert (num_heads == 16 or num_heads == 128), (
+            f"Aiter MLA only supports 16 or 128 number of heads.\n"
+            f"Provided {num_heads} number of heads.\n"
+            "Try adjusting tensor_parallel_size value.")
         unsupported_features = [
             alibi_slopes, sliding_window, blocksparse_params, logits_soft_cap
         ]
@@ -189,7 +202,18 @@ def _forward_decode(
 
         kv_buffer = kv_c_and_k_pe_cache.unsqueeze(2)
 
+        if self.num_heads == 16:
+            # AITER MLA decode kernel only supports
+            # max_seqlen_q=1 when using 16 heads.
+            max_seqlen_qo = 1
+        else:
+            # AITER MLA decode Kernel handles arbitrary
+            # max_seqlen_q values when using 128 heads.
+            assert attn_metadata.prefill is not None
+            max_seqlen_qo = attn_metadata.prefill.max_query_len
+
         aiter_mla_decode_fwd(q, kv_buffer, o, self.scale,
+                             attn_metadata.decode.qo_indptr, max_seqlen_qo,
                              attn_metadata.decode.paged_kv_indptr,
                              attn_metadata.decode.paged_kv_indices,
                              attn_metadata.decode.paged_kv_last_page_len)