fix: critical config + tuning corrections from CCCL source analysis

computility-run.yaml:
  max-num-seqs 1→256: benchmark sweeps [128,256] concurrent seqs,
    current config processes 1 while 127 queue. KV cache budget:
    256 seqs × 2048 tokens × 80KB/token = 41.9GB < 45GB available.
  max-num-batched-tokens 8192→32768: support 256 concurrent prefills.
  gpu-memory-utilization 0.9→0.95: provide KV cache headroom.

Dockerfile:
  Deploy paged_attention_v2_triton.py to vllm package path so
  try-triton-first logic in _custom_ops.py can find it. Falls back
  to PyTorch V2 automatically if Triton V2 fails (SMEM/runtime).

muh/tuning/common.cuh:
  scale_mem_bound max_smem now a parameter (default 48KB). Allows
  policy_selectors to pass hw.max_shared_memory_per_block if actual
  SMEM differs from CCCL 48KB assumption.

muh/tuning/tuning_transform.cuh:
  bytes_in_flight 16KB→32KB. Old derivation used 900/50=18 GB/s/SM
  (wrong, SM=16 confirmed). Actual per-SM BW = 56 GB/s.
  32KB is estimate pending benchmark sweep.

SM count 50→16 corrections across all affected files.

computility-run.yaml

@@ -10,16 +10,16 @@ command:
     - --max-model-len
     - '100000'
     - --gpu-memory-utilization
-    - '0.9'
+    - '0.95'
     - --trust-remote-code
     - -tp
     - '4'
     - --max-num-seqs
-    - '1'
+    - '256'
     - --disable-log-requests
     - --disable-frontend-multiprocessing
     - --max-num-batched-tokens
-    - '8192'
+    - '32768'
     - --enable-chunked-prefill
     - --max-seq-len-to-capture
     - '32768'