[fix][cpu] fix prefill attention in CPU attention backend (#27035)

Signed-off-by: Fadi Arafeh <fadi.arafeh@arm.com>

vllm/engine/arg_utils.py

@@ -1293,7 +1293,8 @@ class EngineArgs:
 
         # Set default arguments for V1 Engine.
         self._set_default_args(usage_context, model_config)
-        # Disable chunked prefill for POWER (ppc64le)/ARM/s390x/RISCV CPUs in V1
+        # Disable chunked prefill and prefix caching for:
+        # POWER (ppc64le)/ARM/s390x/RISCV CPUs in V1
         if current_platform.is_cpu() and current_platform.get_cpu_architecture() in (
             CpuArchEnum.POWERPC,
             CpuArchEnum.S390X,
@@ -1306,6 +1307,13 @@ class EngineArgs:
                 "disabling it for V1 backend."
             )
             self.enable_chunked_prefill = False
+            logger.info(
+                "Prefix caching is not supported for ARM and POWER, "
+                "S390X and RISC-V CPUs; "
+                "disabling it for V1 backend."
+            )
+            self.enable_prefix_caching = False
+
         assert self.enable_chunked_prefill is not None
 
         sliding_window: int | None = None

vllm/v1/attention/backends/cpu_attn.py

@@ -412,7 +412,7 @@ class TorchSDPAMetadataBuilderV1(AttentionMetadataBuilder[TorchSDPAMetadata]):
             num_decode_tokens=num_decode_tokens,
             slot_mapping=slot_mapping,
             # to ensure inference when chunked_prefill is disabled
-            seq_lens=seq_lens_cpu.tolist(),
+            seq_lens=seq_lens_cpu.tolist()[num_decodes:],  # prefill
             decode_seq_lens_tensor=seq_lens_cpu[:num_decodes],  # decode
             decode_max_seq_len=max_decode_seq_len,  # decode
             decode_block_tables=block_table_tensor[:num_decodes],  # decode
@@ -617,7 +617,6 @@ class TorchSDPABackendImpl(AttentionImpl[TorchSDPAMetadata]):
                     prefill_meta.prefill_block_tables,
                     self.alibi_slopes,
                 )
-
         if decode_meta := attn_metadata.decode_metadata:
             assert attn_type != AttentionType.ENCODER_ONLY, (
                 "Encoder-only models should not have decode metadata."
@@ -686,7 +685,12 @@ class TorchSDPABackendImpl(AttentionImpl[TorchSDPAMetadata]):
         causal_attn = attn_type == AttentionType.DECODER
 
         seq_lens_q, seq_lens_kv = attn_metadata.get_seq_lens(attn_type)
-        start_q, start_kv = 0, 0
+        # Incoming Q and KV contain decoded tokens as well, hence start at an offset
+        # equal to num_decode_tokens since decode requests appear first
+        start_q, start_kv = (
+            attn_metadata.num_decode_tokens,
+            attn_metadata.num_decode_tokens,
+        )
         for seq_len_q, seq_len_kv, mask in zip(seq_lens_q, seq_lens_kv, attn_masks):
             end_q = start_q + seq_len_q
             end_kv = start_kv + seq_len_kv