Kernel-launch sync (ADR-0009 D5) and IPCQ drain at inbound (ADR-0023)

- KernelLaunchMsg gains target_start_ns: IO_CPU stamps a global barrier
  (max path latency across every target PE), M_CPU passes it through,
  PE_CPU yields until it before recording pe_exec_start. Every PE in a
  launch begins kernel execution at the same env.now regardless of its
  dispatch path length — eliminates per-PE dispatch-offset artifact in
  cross-PE and cross-cube latency measurements.

- PE_DMA._handle_ipcq_inbound now pays Transaction.drain_ns at the top,
  matching the terminal-drain behavior of ComponentBase._forward_txn for
  every non-IPCQ Transaction. SRC-side tl.send stays fire-and-forget
  (sender doesn't yield on sub_done); tl.recv now blocks until bytes
  have actually drained into its inbox.

- ComponentContext: new compute_path_latency_ns helper + node_overhead_ns
  field populated by GraphEngine.

- tests/test_kernel_launch_sync.py: asserts all PEs in one launch
  produce identical pe_exec_ns for a no-op kernel (zero spread).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-04-23 15:30:29 -07:00
parent 6918e6e906
commit 14d800b0ae
14 changed files with 409 additions and 17 deletions
@@ -162,7 +162,11 @@ class MCpuComponent(ComponentBase):
Routes through find_node_path (M_CPU → NOC → PE_CPU command edges).
PE_CPU sends ResponseMsg back via NOC → M_CPU on completion.
Then sends aggregate ResponseMsg back to IO_CPU on the reverse path.
ADR-0009 D5: stamps target_start_ns so every PE in this fanout
starts executing at the same env.now regardless of dispatch path.
"""
import dataclasses
request = txn.request
target_pe = getattr(request, "target_pe", "all")
cube_prefix = self.node.id.rsplit(".", 1)[0] # e.g. "sip0.cube0"
@@ -172,9 +176,10 @@ class MCpuComponent(ComponentBase):
txn.done.succeed()
return
# Fan out to each PE_CPU, using response-based aggregation
sub_txns: list[Transaction] = []
n_dispatched = 0
# Resolve per-PE paths. If IO_CPU already stamped a global
# target_start_ns (ADR-0009 D5 extended), pass it through.
per_pe: list[tuple[int, list[str], float]] = []
max_latency = 0.0
for pe_id in pe_ids:
pe_cpu_id = f"{cube_prefix}.pe{pe_id}.pe_cpu"
try:
@@ -183,8 +188,24 @@ class MCpuComponent(ComponentBase):
continue
if len(path) < 2:
continue
latency = self.ctx.compute_path_latency_ns(path, nbytes=0)
per_pe.append((pe_id, path, latency))
if latency > max_latency:
max_latency = latency
if getattr(request, "target_start_ns", None) is not None:
stamped_request = request
else:
stamped_request = dataclasses.replace(
request, target_start_ns=float(env.now) + max_latency,
)
# Fan out to each PE_CPU, using response-based aggregation
sub_txns: list[Transaction] = []
n_dispatched = 0
for pe_id, path, _lat in per_pe:
sub_txn = Transaction(
request=request, path=path, step=0,
request=stamped_request, path=path, step=0,
nbytes=0, done=env.event(),
)
yield self.out_ports[path[1]].put(sub_txn.advance())