feat: add XAttention sparse policy integration

Integrate COMPASS XAttention algorithm into nano-vllm's CPU offload
execution path. Uses FlashAttention with native GQA support for
offload mode.

New files:
- nanovllm/kvcache/sparse/utils.py: find_blocks_chunked() utility
- nanovllm/kvcache/sparse/kernels.py: Triton kernels for XAttention
- nanovllm/kvcache/sparse/xattn.py: XAttentionPolicy implementation

Modified:
- nanovllm/config.py: Add XATTN configuration parameters
- nanovllm/engine/model_runner.py: Support XATTN policy
- nanovllm/kvcache/sparse/__init__.py: Register XAttentionPolicy
- tests/test_ruler.py: Add --sparse-policy parameter

Test results (32k ruler):
- NIAH tasks: 12/12 (100%)
- QA/Recall tasks: 11/15 (73%)
- Overall: 23/27 (85%)

Co-Authored-By: Claude <noreply@anthropic.com>

nanovllm/config.py

@@ -10,6 +10,7 @@ class SparsePolicyType(Enum):
     FULL = auto()   # No sparse attention (load all blocks)
     QUEST = auto()  # Query-aware Top-K block selection (decode only)
     MINFERENCE = auto()  # MInference vertical + slash sparse prefill (GPU-only)
+    XATTN = auto()  # XAttention chunked estimation + block-sparse attention
 
 
 @dataclass
@@ -53,6 +54,15 @@ class Config:
     minference_num_sink_tokens: int = 30  # Sink tokens to always keep
     minference_num_recent_diags: int = 100  # Recent diagonals to always keep
 
+    # XAttention configuration (used when sparse_policy == XATTN)
+    xattn_stride: int = 8  # Stride for reorganizing Q/K
+    xattn_threshold: float = 0.9  # Block selection threshold (0-1)
+    xattn_chunk_size: int = 16384  # Chunk size for estimation (auto if None)
+    xattn_use_triton: bool = True  # Use Triton kernels (requires SM 80+)
+    xattn_keep_sink: bool = False  # Always keep first block (sink tokens)
+    xattn_keep_recent: bool = False  # Always keep recent diagonal blocks
+    xattn_norm: float = 1.0  # Normalization factor for attention scores
+
     def __post_init__(self):
         assert os.path.isdir(self.model)
         assert self.kvcache_block_size % 256 == 0