Support FP8 KVCache on XPU (#37731)

Signed-off-by: Xinyu Chen <xinyu1.chen@intel.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>

.buildkite/intel_jobs/test-intel.yaml

@@ -35,6 +35,7 @@ steps:
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager -tp 2 --distributed-executor-backend mp &&
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --attention-backend=TRITON_ATTN &&
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --quantization fp8 &&
+        python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --kv-cache-dtype fp8 &&
         python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --block-size 64 --enforce-eager --max-model-len 8192 &&
         python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 &&
         python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel'

vllm/_xpu_ops.py

@@ -258,6 +258,9 @@ class xpu_ops:
             # alibi_slopes = alibi_slopes,
             # softcap=softcap,
             return_softmax_lse=return_softmax_lse,
+            q_descale=q_descale,
+            k_descale=k_descale,
+            v_descale=v_descale,
         )
 
     @staticmethod

vllm/v1/attention/backends/fa_utils.py

@@ -166,12 +166,18 @@ def is_fa_version_supported(fa_version: int) -> bool:
 
 
 def flash_attn_supports_fp8() -> bool:
+    if current_platform.is_xpu():
+        return True
     return (
         get_flash_attn_version() == 3
         and current_platform.is_device_capability_family(90)
     )
 
 
+def flash_attn_supports_quant_query_input() -> bool:
+    return not current_platform.is_xpu()
+
+
 def flash_attn_supports_sinks() -> bool:
     if current_platform.is_xpu():
         return True

vllm/v1/attention/backends/flash_attn.py

@@ -20,6 +20,7 @@ from vllm.v1.attention.backend import (
 )
 from vllm.v1.attention.backends.fa_utils import (
     flash_attn_supports_fp8,
+    flash_attn_supports_quant_query_input,
     get_flash_attn_version,
     is_fa_version_supported,
     is_flash_attn_varlen_func_available,
@@ -656,7 +657,7 @@ class FlashAttentionImpl(AttentionImpl):
                 "heads in the layer"
             )
 
-        self.supports_quant_query_input = True
+        self.supports_quant_query_input = flash_attn_supports_quant_query_input()
 
         vllm_config = get_current_vllm_config_or_none()
         dcp_a2a = (
@@ -757,7 +758,11 @@ class FlashAttentionImpl(AttentionImpl):
 
             descale_shape = (cu_seqlens_q.shape[0] - 1, self.num_kv_heads)
 
-            q_descale = layer._q_scale.expand(descale_shape)
+            q_descale = (
+                layer._q_scale.expand(descale_shape)
+                if self.supports_quant_query_input
+                else None
+            )
             k_descale = layer._k_scale.expand(descale_shape)
             v_descale = layer._v_scale.expand(descale_shape)