ADR-0009 D5: chain-aware target_start_ns + zero-byte launch fanout

The single-walk predictor (find_node_path(io_cpu, pe_cpu) +
compute_path_latency_ns) under-shot actual dispatch latency for far
cubes -- the routing graph could pick a path bypassing M_CPU, and
non-zero-nbytes launch sub-txns serialized on shared first hops.
Far PEs arrived at _execute_kernel after target_start_ns, silently
skipped the barrier yield, and started pe_exec_start late. Their
reported pe_exec_ns under-counted by exactly the late_ns amount
(63 ns observed at h4 cube4.pe0 in the IPCQ test, up to 113 ns
worst case for cubes 9-11), producing the suspicious flat region
in the h4 IPCQ curve at 8192/10240 bytes.

Fix:
  - IO_CPU predictor uses the explicit two-leg chain
    (IO_CPU->M_CPU + M_CPU->PE_CPU - io.overhead - m.overhead), so
    every PE on every targeted cube has a barrier >= its real
    dispatch arrival.
  - Kernel-launch fanout sub-txns carry nbytes=0 (control-plane,
    not data-plane), removing the per-cube fanout serialization
    that pushed far M_CPUs past the predictor.
  - Legacy io_cpu mirror updated.

ADR-0009 D5 mechanism updated to specify the two-leg formula and
the nbytes=0 requirement. New tests/test_d5_barrier_invariant.py
asserts (a) no PE enters _execute_kernel after target_start_ns and
(b) every PE in a multi-cube launch has identical pe_exec_start --
both regressions silently pass on the existing
tests/test_kernel_launch_sync.py because that test only inspects
post-aggregation max(pe_exec_ns).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/test_d5_barrier_invariant.py

@@ -0,0 +1,194 @@
+"""ADR-0009 D5 invariant: all PEs targeted by a single kernel launch MUST
+begin executing the kernel body at the same simulated time, regardless of
+their dispatch path length.
+
+These tests directly verify the invariant by capturing per-PE state at the
+top of `_execute_kernel`:
+
+  test_no_pe_arrives_after_target_start_ns
+      Asserts: for every PE that enters _execute_kernel during a multi-cube
+      launch, `env.now` at entry must be <= target_start_ns. Otherwise the
+      PE's barrier yield would be a no-op and `pe_exec_start` would be set
+      late, breaking the D5 "same simulated time" mandate.
+
+  test_all_pes_have_identical_pe_exec_start
+      Asserts: every PE's `pe_exec_start` (the value of `env.now` recorded
+      immediately AFTER the barrier yield) is identical across all PEs in
+      the launch.
+
+Both tests are expected to FAIL today and become the regression check the
+Phase 2 D5 predictor + fallback fix must make pass.
+"""
+from __future__ import annotations
+
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+from kernbench.policy.placement.dp import DPPolicy
+from kernbench.runtime_api.context import RuntimeContext
+from kernbench.runtime_api.types import DeviceSelector
+from kernbench.sim_engine.engine import GraphEngine
+from kernbench.topology.builder import resolve_topology
+
+TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
+
+
+def _capture_per_pe_d5_state():
+    """Monkey-patch PeCpuComponent._execute_kernel to record, per PE:
+
+      - entry_now: env.now at function entry (before any yield)
+      - target_start_ns: the value carried by the request
+      - barrier_yielded: True if the barrier yield fired (entry_now < target)
+      - pe_exec_start: env.now immediately after the barrier check
+                       (i.e. the value the original code sets)
+
+    Returns (records: list[dict], restore: callable).
+    """
+    import kernbench.components.builtin.pe_cpu as pe_cpu_mod
+
+    records: list[dict] = []
+    original = pe_cpu_mod.PeCpuComponent._execute_kernel
+
+    def patched(self, env, txn):
+        request = txn.request
+        target_start = getattr(request, "target_start_ns", None)
+        entry_now = float(env.now)
+        rec = {
+            "node_id": self.node.id,
+            "entry_now": entry_now,
+            "target_start_ns": (
+                float(target_start) if target_start is not None else None
+            ),
+            "barrier_yielded": (
+                target_start is not None
+                and float(target_start) > entry_now
+            ),
+            "pe_exec_start": None,  # filled below by sniff
+            "late_ns": (
+                None if target_start is None
+                else max(0.0, entry_now - float(target_start))
+            ),
+        }
+        records.append(rec)
+
+        # We can't easily inject a callback at the original's
+        # `pe_exec_start = env.now` line without rewriting it. Approximate:
+        # if the original yields the barrier, env.now after the yield is
+        # target_start_ns; otherwise pe_exec_start is entry_now (skipped).
+        if rec["barrier_yielded"]:
+            rec["pe_exec_start"] = float(target_start)
+        else:
+            rec["pe_exec_start"] = entry_now
+
+        yield from original(self, env, txn)
+
+    pe_cpu_mod.PeCpuComponent._execute_kernel = patched
+
+    def restore():
+        pe_cpu_mod.PeCpuComponent._execute_kernel = original
+
+    return records, restore
+
+
+def _run_multicube_launch():
+    """Drive a no-op kernel launch across all 16 cubes x 8 PEs and return
+    the per-PE D5 records collected by the monkey-patch."""
+    records, restore = _capture_per_pe_d5_state()
+    try:
+        topo = resolve_topology(str(TOPOLOGY_PATH))
+        engine = GraphEngine(topo.topology_obj, enable_data=True)
+        spec = topo.topology_obj.spec
+
+        with RuntimeContext(
+            engine=engine, target_device=DeviceSelector("all"),
+            correlation_id="d5_barrier", spec=spec,
+        ) as ctx:
+            dp = DPPolicy(
+                cube="row_wise", pe="column_wise",
+                num_cubes=16, num_pes=8,
+            )
+
+            def kernel(t_ptr, n_elem, tl):
+                pass  # no-op
+
+            ctx.ahbm.set_device(0)
+            t = ctx.zeros(
+                (16, 8 * 64), dtype="f16", dp=dp, name="probe",
+            )
+            t.copy_(ctx.from_numpy(
+                np.zeros((16, 8 * 64), dtype=np.float16),
+            ))
+
+            pending = ctx.launch(
+                "d5_probe", kernel, t, 64, _defer_wait=True,
+            )
+            for h, _sip, meta in pending:
+                ctx.wait(h, _meta=meta)
+    finally:
+        restore()
+    return records
+
+
+def test_no_pe_arrives_after_target_start_ns():
+    """ADR-0009 D5: no PE may enter `_execute_kernel` after target_start_ns.
+
+    Today this fails because IO_CPU's predictor under-shoots actual
+    dispatch latency for far cubes (cube4, cube9-15). Phase 2 fix:
+    chain-aware predictor in IO_CPU + monotonic upward re-stamp in M_CPU.
+    """
+    records = _run_multicube_launch()
+    assert records, "expected per-PE _execute_kernel records"
+
+    late = [
+        r for r in records
+        if r["target_start_ns"] is not None
+        and r["late_ns"] is not None
+        and r["late_ns"] > 1e-6
+    ]
+
+    if late:
+        # Provide actionable diagnostic in the failure.
+        worst = sorted(late, key=lambda r: -r["late_ns"])[:5]
+        details = "\n".join(
+            f"  {r['node_id']}: late by {r['late_ns']:.2f} ns "
+            f"(entry_now={r['entry_now']:.2f}, "
+            f"target_start_ns={r['target_start_ns']:.2f})"
+            for r in worst
+        )
+        pytest.fail(
+            f"ADR-0009 D5 violated: {len(late)}/{len(records)} PEs "
+            f"entered _execute_kernel AFTER target_start_ns "
+            f"(barrier yield silently skipped). "
+            f"Worst offenders:\n{details}"
+        )
+
+
+def test_all_pes_have_identical_pe_exec_start():
+    """ADR-0009 D5: every PE's pe_exec_start must be identical.
+
+    With D5 honored, every PE either yields to target_start_ns (start =
+    target_start_ns) or, if late, would still be aligned by the M_CPU
+    upward re-stamp (Phase 2). Today: 75/128 PEs in this launch have
+    distinct pe_exec_start values because they skipped the barrier.
+    """
+    records = _run_multicube_launch()
+    assert records, "expected per-PE _execute_kernel records"
+
+    starts = sorted({round(r["pe_exec_start"], 6) for r in records})
+    if len(starts) > 1:
+        spread = max(starts) - min(starts)
+        # Distribution of how many PEs at each distinct start time
+        from collections import Counter
+        bucket = Counter(round(r["pe_exec_start"], 6) for r in records)
+        details = "\n".join(
+            f"  pe_exec_start={t}: {n} PEs"
+            for t, n in sorted(bucket.items())
+        )
+        pytest.fail(
+            f"ADR-0009 D5 violated: PEs have {len(starts)} distinct "
+            f"pe_exec_start values (spread = {spread:.2f} ns); "
+            f"D5 mandates a single common value. "
+            f"Distribution:\n{details}"
+        )