examples: distributed collective zoo tutorials (steps 12-16) + walkthroughs + CI

[georgebisbas]

Summary

Third PR of the distributed teaching ladder: the collective zoo + composition. Four small, golden-validated programs (steps 12–15) each hand-roll a collective from the substrate — broadcast, allgather, reduce_scatter, all_to_all — then reveal its builtin (--mode hand|builtin), and step 16 composes broadcast + allreduce + allgather in one kernel. Each step ships a walkthrough page (en + zh) and CI legs at P=2 and P=4.

Single squashed commit (78dfb505) on current main — the diff is only this
PR's own files (25 files: 5 examples, walkthroughs 17–21 en + zh, tutorial
index/cross-link updates, mkdocs nav, CI legs). Review rounds from #2330 and
this PR's own Codex/CodeRabbit rounds are all addressed; see Corrections
below.

Tutorial steps (this PR)

Step	Program	Teaches
12	12_broadcast.py	One-to-all: root stages, barrier, every rank reads root; reveal pld.tensor.broadcast
13	13_allgather.py	All-to-all slices: stage your row, barrier, gather every row; reveal pld.tensor.allgather (the all-gather half of two-phase)
14	14_reduce_scatter.py	All-to-chunks: stage all chunks, barrier, sum your chunk across peers; reveal pld.tensor.reduce_scatter (the reduce-scatter half of two-phase)
15	15_all_to_all.py	Personalized exchange: put a distinct slice per destination, barrier, read back; reveal pld.tensor.all_to_all
16	16_putting_it_together.py	Capstone: compose broadcast + allreduce + allgather in one kernel, one signal per collective (a teaching choice)

Steps 12–15 build their program from a (nr, use_builtin) factory; step 16
from (nr). One source serves any P via -d, sim-validated at P=2 and P=4 in
both modes.

Corrections carried over from the #2330 review

Both points Yunji raised on the all-reduce ladder applied here too, and are
fixed in this commit:

• The factory rationale was wrong in all five files — each claimed the
  factory exists because the [nr, 1] signal and [nr, SIZE] windows "must be
  statically known". None of those is a tile shape, so none forces a
  compile-time rank count. Verified rather than argued: every one of the five
  was rebuilt with NR = pl.dynamic("NR") plus pld.nranks(ctx) /
  pld.world_size() and run at P=4 in both modes — all five compile and pass
  their goldens. The real reason 12–15 need a factory is use_builtin:
  host_orch branches on it to choose which per-device orchestrator to
  dispatch, so it must be a Python constant when the body is traced. Step 16
  has no mode flag and so no requirement at all; its docstring says so and
  notes it could become a module-level program.
• Rank-count spelling now follows the convention the all-reduce steps
  converged on: nranks = pld.nranks(ctx) for kernel loop bounds,
  pld.world_size() in host orchestration, nr left only where a shape wants
  a literal. The 17–21 snippets (en + zh) are updated to match the source they
  quote.

Also repaired three defects that predated the rebase: a spliced
## Suggested reading order heading in 05-tutorials.md (en) that left a
dangling ship together line and a superseded "12–16 remain planned" sentence
contradicting the table below it, and two stale "steps 08–16 are planned"
pointers in 12-dynamic_rank_count.md (en + zh).

Review-round corrections (this PR)

The automated reviewers (Codex, CodeRabbit) found real errors in the 17–21
reveal sections, and checking them against lower_composite_ops_pass.cpp
turned up more. All fixed in this commit:

• Allgather is a push, not a pull. The builtin expands to one pld.tile.put
  per peer (row my_rank), then the barrier — no remote_load. The hand
  version is a pull with the barrier before the transfer; the builtin pushes
  with the barrier after. The page now teaches the diff instead of denying it
  (hand: P remote_loads, self included).
• Reduce-scatter is Sum-only and carries a second post-reduce barrier (WAR
  prevention before storing into target[my_rank]). The page advertises the
  Sum contract, not the full ReduceOp family.
• The "fatal pitfall — never reuse a signal" was false. All four InCore
  composites end in EmitEpilogueReset, so back-to-back reuse of one [nr, 1]
  signal is safe (tested at P=2 and P=4). The real hazard is sharing one window
  across two signal layouts, plus the HOST-builtin-in-a-loop restriction; the
  pitfall now says that, and the kernel's three signals are a teaching choice.
• Mesh allreduce traffic is (P-1)·N (step 16 pins mode="mesh"), not the
  two-phase 2·(P-1)/P·N; the cost card now carries the right term.
• Code review also aligned step 16's module docstring with the self-clearing
  protocol (the "signals do not self-reset" claim was stale).

Docs

• docs/en+zh/user/distributed/17-broadcast.md … 21-putting_it_together.md
  — one walkthrough per step (The idea → Run it → Walkthrough → Edge cases →
  See also, cost card + fatal-pitfall + three-column debugging table each;
  each ships a narrative IR-diff teaching artifact).
• docs/en+zh/user/distributed/05-tutorials.md — steps 12–16 marked ✅ shipped;
  the full 16-step ladder now ships together.
• Cross-links: 01-collectives.md §Runnable Examples (broadcast/allgather/
  reduce_scatter/all_to_all rows → the walkthroughs), 02-primitives.md
  shipped note; the all_to_all page links 03-execution.md,
  examples/runtime/distributed_callback.py, and the pypto-lib applications
  (AllGather-GEMM feat(codegen): Enable a2a3 up/down split cross-core pipe codegen #869, distributed MoE) by name.
• mkdocs.yml — nav entries for 17–21.

CI

• examples-tests gains the legs for steps 12–16: P=2 default
  (loop), P=2 builtin reveal, and P=4 in both modes — every documented
  invocation is CI-validated.
• Docs gates (nav, en/zh parity, pre-commit, mkdocs build --strict) green.

Verification

• All 18 CI-documented invocations of steps 12–16 pass on a2a3sim (P=2 and
  P=4, hand and builtin), goldens vs torch with tolerance — re-run after the
  rank-count change, not just before it.
• pre-commit (22 hooks) and mkdocs build --strict clean on the squashed
  head 78dfb505.
• Developer gate: 4-card NPU run (-p a2a3 -d 0,1,2,3) via task-submit
  where available; else 2-card + sim-P=4 evidence.

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📝 Walkthrough

Walkthrough

The change adds distributed examples for broadcast, allgather, reduce-scatter, all-to-all, and composition. It adds English and Chinese tutorials, updates tutorial indexes, registers navigation entries, and extends simulator CI coverage.

Changes

Collective examples and tutorials

Layer / File(s)	Summary
Broadcast and AllGather examples examples/distributed/12_broadcast.py, examples/distributed/13_allgather.py, docs/{en,zh}/user/distributed/{17-broadcast,18-allgather}.md	Adds hand-rolled and builtin implementations, orchestration, CLI execution, validation, and tutorials for Broadcast and AllGather.
ReduceScatter and AllToAll examples examples/distributed/{14_reduce_scatter,15_all_to_all}.py, docs/{en,zh}/user/distributed/{19-reduce_scatter,20-all_to_all}.md	Adds shared-window reduction and peer exchange examples with builtin modes, golden validation, and tutorials.
Putting-it-together composition examples/distributed/16_putting_it_together.py, docs/{en,zh}/user/distributed/21-putting_it_together.md	Adds a kernel that combines broadcast, mesh allreduce, allgather, and local scaling with separate signal windows and output checks.
Tutorial status and CI integration .github/workflows/ci.yml, docs/{en,zh}/user/distributed/{01-collectives,02-primitives,05-tutorials,12-dynamic_rank_count}.md, mkdocs.yml	Marks steps 12–16 as shipped, links the new pages, adds them to navigation, and runs examples 12–16 in simulator CI.

Estimated code review effort: 4 (Complex) | ~60 minutes

Merge Risk: 🔵 Low · up to 0b2fc

The PR adds the distributed collective tutorials and CI coverage, but several walkthrough details could mislead users about allgather lowering, all-to-all buffer usage, prerequisites, and supported rank counts. The PR is mergeable with explicit owner awareness or a follow-up to correct these localized documentation issues.

Poem

A rabbit hops through ranks in line

Broadcast roots and slices align
Allgather gathers, sums take flight
All-to-all trades rows just right
The capstone joins the signals bright
CI checks the paths tonight

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Docstring Coverage	✅ Passed	Docstring coverage is 86.84% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 38 functions across 5 files. (20 skipped: 2…
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Title check	✅ Passed	The title accurately summarizes the main changes: distributed collective tutorials for steps 12–16, walkthrough documentation, and CI coverage. It is specific and concise enough for repository history…
Description check	✅ Passed	The description is directly related to the changeset. It explains the five examples, English and Chinese walkthroughs, documentation updates, CI coverage, corrections, and verification results.

Full details: Docstring Coverage

Explanation

Docstring coverage is 86.84% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 38 functions across 5 files. (20 skipped: 20 unsupported.)

Full details: Title check

Explanation

The title accurately summarizes the main changes: distributed collective tutorials for steps 12–16, walkthrough documentation, and CI coverage. It is specific and concise enough for repository history.

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Inline comments:
In `@docs/en/user/distributed/18-allgather.md`:
- Around line 93-117: Correct both allgather walkthroughs in
docs/en/user/distributed/18-allgather.md lines 93-117 and
docs/zh/user/distributed/18-allgather.md lines 79-95: describe
builtin_step/LowerCompositeOps as emitting one pld.tile.put per peer followed by
the barrier sequence, returning target; clarify later pl.load calls are local
reads, remove per-peer remote_load and “same schedule” claims, and retain only
the shared rank-indexed row layout.

In `@docs/en/user/distributed/20-all_to_all.md`:
- Around line 133-137: Update the all-to-all documentation to describe the
operation as out-of-place, requiring separate source and target buffers rather
than calling it in-place. Apply the equivalent terminology correction in
docs/en/user/distributed/20-all_to_all.md lines 133-137 and
docs/zh/user/distributed/20-all_to_all.md line 102.

In `@docs/en/user/distributed/21-putting_it_together.md`:
- Around line 6-8: Add 16-allreduce_reveal.md to the prerequisite list in
docs/en/user/distributed/21-putting_it_together.md (lines 6-8) and add the same
localized allreduce prerequisite to
docs/zh/user/distributed/21-putting_it_together.md (line 5); no other changes
are needed.
- Around line 95-97: Update the English wording at
docs/en/user/distributed/21-putting_it_together.md lines 95-97 to say the
gathered data came from all ranks instead of three ranks. Apply the equivalent
all-ranks wording at docs/zh/user/distributed/21-putting_it_together.md lines
75-78, preserving the surrounding explanation.

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📒 Files selected for processing (25)

• .github/workflows/ci.yml
• docs/en/user/distributed/01-collectives.md
• docs/en/user/distributed/02-primitives.md
• docs/en/user/distributed/05-tutorials.md
• docs/en/user/distributed/12-dynamic_rank_count.md
• docs/en/user/distributed/17-broadcast.md
• docs/en/user/distributed/18-allgather.md
• docs/en/user/distributed/19-reduce_scatter.md
• docs/en/user/distributed/20-all_to_all.md
• docs/en/user/distributed/21-putting_it_together.md
• docs/zh/user/distributed/01-collectives.md
• docs/zh/user/distributed/02-primitives.md
• docs/zh/user/distributed/05-tutorials.md
• docs/zh/user/distributed/12-dynamic_rank_count.md
• docs/zh/user/distributed/17-broadcast.md
• docs/zh/user/distributed/18-allgather.md
• docs/zh/user/distributed/19-reduce_scatter.md
• docs/zh/user/distributed/20-all_to_all.md
• docs/zh/user/distributed/21-putting_it_together.md
• examples/distributed/12_broadcast.py
• examples/distributed/13_allgather.py
• examples/distributed/14_reduce_scatter.py
• examples/distributed/15_all_to_all.py
• examples/distributed/16_putting_it_together.py
• mkdocs.yml

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[georgebisbas]

@YunjiQin — this is the follow-up to #2330 (tutorial steps 12–16), now out of draft and rebased onto main since #2330 landed this morning. Flagging you both for review and because of a CI failure that is worth not misreading.

Both points you raised on #2330 apply here, and are fixed

The zoo examples had drifted the same two ways the all-reduce ladder had:

• The factory rationale was wrong in all five files, in exactly the way step 08's was — each claimed the factory exists because the [nr, 1] signal and [nr, SIZE] windows "must be statically known". 12_broadcast.py repeated the sentence step 08 was rewritten to delete, verbatim. None of those is a tile shape.

  Verified rather than argued, per the last round: each of the five was rebuilt with NR = pl.dynamic("NR") plus pld.nranks(ctx) / pld.world_size() and run at P=4 in both modes. All five compile and pass their goldens, so a compile-time nr is required by none of them. What actually forces a factory in 12–15 is use_builtin: host_orch branches on it to pick which per-device orchestrator to dispatch, so it must be a Python constant at trace time. Step 16 has no mode flag and so no requirement at all; its docstring now says so and notes it could become a module-level program.

• Rank-count spelling now follows the convention you proposed: pld.nranks(ctx) in kernels, pld.world_size() in host orchestration, nr left only where a shape wants a literal. The walkthrough snippets in 17–21 were updated to match the source they quote.

A round of walkthrough corrections

The automated reviewers found real errors in the 17–21 reveal sections, and checking them against lower_composite_ops_pass.cpp turned up more. Briefly: allgather is a push (pld.tile.put per peer, then the barrier), not the per-peer reads the page claimed; reduce_scatter is Sum-only and emits a second post-reduce barrier; and the "fatal pitfall — never reuse a signal" was false — all four InCore composites end in EmitEpilogueReset, and a variant of step 16 driving all three collectives through one shared [nr, 1] signal passes at P=2 and P=4. That callout had been telling readers to allocate windows they do not need.

Details are in the two commit messages and in the inline replies.

The red check is not this PR

examples-tests fails on docs/en/user/performance/01-task-granularity.md:161 — a main-owned doc block this PR does not touch, in a file unchanged since #2394. Everything else is green (14 checks, including dist-system-tests, codegen-tests, system-tests* and docs-examples).

Three runs over identical content:

run	runner	result
32956862246	infra024-cpu-x64-5	FAIL — 39/16384, greatest abs diff 0.0258941650390625 @ (21, 67)
32971642842	infra024-cpu-x64-5	PASS (doc-block step confirmed to have run)
32974197741	infra024-cpu-x64-4	FAIL — 38/16384, identical diff at the identical index

Same runner produces both outcomes, so it is not host-arch- or runner-related — I had initially suspected #2525 unpinning runs-on from arm64, and the same-runner pass refutes that. And a bit-identical worst-case error that sometimes disappears is not runtime jitter on a seeded elementwise add + exp. It looks like the kernel binary differing between builds (ccache hit/miss, toolchain resolution, or similar), with the assertion too tight to absorb it: the block's expected values reach 253, where rtol=1e-4, atol=1e-4 allows only ~0.017 absolute.

I have deliberately not touched that file here — widening a tolerance from an unrelated PR would hide the build-nondeterminism question, and the file is not ours. Happy to send a one-line fix on main as its own PR if that is the preferred route, but the underlying "same source, two different kernels" is the part I think is worth someone's attention.

Review whenever suits you.

[georgebisbas]

@YunjiQin — correcting my earlier comment on the CI failure. I had the cause right, then talked myself out of it, and the version I posted was wrong in the details. The real answer is documented in this repo and I should have found it sooner.

What it actually is. The failing block is a live reproducer for a known simulator-state contamination bug, and .github/workflows/ci.yml says so in the examples-tests job:

Identical input and identical binary must not produce different device output.

It is the job shape, not the host alone. docs-examples runs the very same run_doc_examples.py invocation on the very same hosts and has passed every time, and the difference is that there the doc blocks are the first simulator work in the job, whereas here they run after the distributed ladder (-d 0,1,2,3) and the teaching examples. Prior simulator activity in the same job is contaminating the later run, which also explains why the count of wrong elements moves while the extremes do not.

That matches every measurement I took independently — bit-identical worst-case error with a varying mismatch count, docs-examples green while examples-tests fails on the same commit — I just attributed it to exp tolerance instead of finding the existing diagnosis.

Why this PR hit it and others didn't. examples-tests was pinned to aarch64 precisely to keep that signal stable. #2525 (ec5d20c1) removed the pin on 2026-08-26; this branch was rebased inside that window, so the job landed on x86_64 and reproduced the contamination. #2485 (60c3e535) restored the pin today.

Fix: rebased onto current main, which carries the restored pin — now at 7ec0f178. No content change; the diff is unchanged at 25 files.

Two retractions, so nothing misleading is left standing:

1. My earlier claim that this was "a main-owned flake, nothing to do with this PR" was right in substance but wrong in reasoning — I blamed a too-tight exp tolerance and pointed at ci: support mixed-architecture self-hosted runners and bound the shared uv cache #2525 only as a suspicion I then withdrew. ci: support mixed-architecture self-hosted runners and bound the shared uv cache #2525 was in fact the trigger.
2. I then swung the other way and suggested the failure might be caused by this PR's content. That was also wrong. The one real connection is job shape: this PR adds simulator legs ahead of the doc-block step, which is exactly the contamination trigger the comment describes — so it raises exposure, but neither the cause nor the fix is here.

I also opened #2552 to loosen that tolerance and have closed it — it would have accepted the contaminated output and destroyed the signal. Codex caught that; credit where due.

Nothing outstanding on this PR from my side.