feat(gqa): Case-6 composite-command decode variants + on-chip-operand DMA fix

Add two command-form variants of the Case-6 (Cube-SP x PE-SP) long-context
decode kernel alongside the primitive baseline:
  - composite: per-tile GEMMs issued as one coarse tl.composite over the
    full S_local (PE_SCHEDULER tiles/streams K,V) -- O(1) PE_CPU commands
    vs the primitive kernel's O(n_tiles).
  - composite_extended: Q.K^T composite + softmax_merge recipe composite
    (ADR-0065), folding the per-tile online merge + P.V.

Extract the shared two-level (m,l,O) reduce into _gqa_mlo_reduce and
refactor the baseline to use it (byte-equal, guarded by a 64-rank
command-stream digest test).

Engine fix: _make_compute_out omitted pinned=True, so an on-chip TCM
compute result consumed as a composite GEMM operand was scheduled as an
HBM DMA_READ of its bit-61 scratch address -> PhysAddrError in data mode.
Mark compute outputs pinned (resident), matching the composite
auto-output and recipe scratch handles. .pinned is read only by the
tiling DMA gate, so this is byte-equal for existing benches.

Add the composite sweep (emit-level PE_CPU dispatch to 1M + data-mode
latency to 128K), its plot, umbrella wiring (GQA_1H_SWEEPS=composite),
and tests (refactor guard, dispatch saturation, engine-fix, e2e).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

src/kernbench/benches/milestone_1h_gqa.py

@@ -8,12 +8,13 @@ Currently exercises (long-context only — short-context panels are
 future work):
   - 4-cases prefill comparative study (gqa_helpers.long_ctx.gqa_prefill_long_ctx_4cases)
   - 4-cases decode comparative study  (gqa_helpers.long_ctx.gqa_decode_long_ctx_4cases)
+  - Case-6 composite-command study    (gqa_helpers.long_ctx.gqa_decode_long_ctx_composite)
 
-Each sub-sweep writes its own ``sweep_{prefill,decode}.json`` into the
-shared output dir ``benches/1H_milestone_output/gqa/gqa_long_ctx/``.
+Each sub-sweep writes its own ``sweep_*.json`` into the shared output
+dir ``benches/1H_milestone_output/gqa/gqa_long_ctx/``.
 Selection via the env var ``GQA_1H_SWEEPS=prefill,decode`` (default
-runs both). Toggle individual sweeps with ``GQA_1H_SWEEPS=prefill``
-or ``GQA_1H_SWEEPS=decode``.
+runs prefill+decode). The composite study is opt-in (it sweeps the
+data-mode engine over several S_kv points): ``GQA_1H_SWEEPS=composite``.
 
 Gated by ``GQA_1H_RUN=1`` to keep CI fast.
 """
@@ -24,6 +25,9 @@ import os
 from kernbench.benches.gqa_helpers.long_ctx.gqa_decode_long_ctx_4cases import (
     run_sweep as _run_decode_sweep,
 )
+from kernbench.benches.gqa_helpers.long_ctx.gqa_decode_long_ctx_composite import (
+    run_sweep as _run_composite_sweep,
+)
 from kernbench.benches.gqa_helpers.long_ctx.gqa_prefill_long_ctx_4cases import (
     run_sweep as _run_prefill_sweep,
 )
@@ -57,6 +61,7 @@ def run(torch) -> None:
     runners = {
         "prefill": _run_prefill_sweep,
         "decode": _run_decode_sweep,
+        "composite": _run_composite_sweep,
     }
     unknown = [s for s in sweeps if s not in runners]
     if unknown: