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>
This commit is contained in:
2026-04-27 15:12:58 -07:00
parent 90874abbfe
commit c1a5cf3a2a
4 changed files with 275 additions and 19 deletions
@@ -86,11 +86,36 @@ Mechanism.
- `KernelLaunchMsg` carries an optional `target_start_ns: float | None`.
- **IO_CPU** is the canonical stamper. On fan-out to M_CPUs, it
computes `target_start_ns = env.now + max_latency` where `max_latency`
is the maximum `ComponentContext.compute_path_latency_ns(path)` across
every target (sip, cube, pe) tuple — `path = find_node_path(io_cpu,
pe_cpu_id)`. The stamped value is placed on the request carried by
every fanned-out sub-Transaction.
computes `target_start_ns = env.now + max_latency` where
`max_latency` is the maximum, over every target (sip, cube, pe)
tuple, of the **two-leg dispatch chain**:
```
max_latency(sip, cube, pe) =
compute_path_latency_ns(find_node_path(io_cpu, m_cpu(sip, cube)))
+ compute_path_latency_ns(find_node_path(m_cpu(sip, cube), pe_cpu))
- io_cpu.overhead_ns
- m_cpu.overhead_ns
```
This models the actual dispatch as **two sequential Transactions**
(IO_CPU → M_CPU, then M_CPU → PE_CPU). Each leg's
`compute_path_latency_ns` adds its endpoints' `overhead_ns`;
`io_cpu.overhead_ns` is subtracted because IO_CPU has already
paid it before this method runs, and `m_cpu.overhead_ns` is
subtracted once because it appears as endpoint of leg1 *and*
start of leg2 but is paid only once at run time. A single
`find_node_path(io_cpu, pe_cpu)` walk is **not** equivalent —
it can pick a graph path that bypasses M_CPU and silently
under-shoots the prediction for far cubes, breaking the D5
invariant.
The fanned-out sub-Transactions carry **`nbytes = 0`** for
`KernelLaunchMsg` (control message only). Without this,
large kernel-launch payloads would occupy fabric BW on the
shared first hop and serialize the per-cube dispatch, pushing
far M_CPUs past `target_start_ns` and re-introducing the
late-arrival violation.
- **M_CPU** passes an already-stamped `target_start_ns` through
unchanged. Only when the value is absent (e.g. a direct
launch-to-M_CPU unit test) does M_CPU compute a per-cube barrier