fix: revert invalid patches, add honest tuning surface assessment

REVERTED (invalid):
- paged_attn.py: restored use_v1=True hardcode. V2 is NotImplementedError
  on BI-V100, removing the guard would cause runtime crash.
- fused_moe.py: BLOCK_SIZE_N/K changes reverted. ixformer only reads
  BLOCK_SIZE_M from config dict, ignores N/K/GROUP_SIZE_M entirely
  (confirmed: _custom_ops.py:774 only passes config['BLOCK_SIZE_M']).
- _custom_ops.py: SMEM change reverted pending hardware confirmation.
- triton_flash_attention.py: autotune configs reverted (will re-add properly).
- prefix_prefill.py: comment enhancement reverted (was harmless but noisy).

ADDED:
- TUNING_SURFACE_TRUTH.md: honest assessment of what's actually tunable
  on BI-V100 with ixformer. Documents that bench_bi100.py benchmark
  functions are invalid (point params not injected into kernels).

Actual tuning surface is 5 parameters, not dozens:
  1. BLOCK_SIZE_M (fused_moe, passes to ixformer)
  2. use_v1 threshold (hardcoded True, V2 unimplemented)
  3. BLOCK/NUM_WARPS (prefix_prefill Triton JIT)
  4. SMEM declaration (affects Triton compiler)
  5. autotune config set (triton_flash_attention)

vllm/attention/ops/triton_flash_attention.py

@@ -302,29 +302,6 @@ def _attn_fwd_inner(
             num_stages=1,
             num_warps=4,
         ),
-        # muh: BI-V100 configs (SM=16, 48KB SMEM, 900GB/s BW)
-        # SM=16 → fewer CTAs → favor configs with moderate BLOCK_M
-        # to maintain occupancy without excessive SMEM per CTA.
-        triton.Config(
-            {
-                "BLOCK_M": 64,
-                "BLOCK_N": 32,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 32,
-                "BLOCK_N": 64,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
     ],
     key=['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL'],
 )