Rename the intercube all-reduce identity to lrab_hierarchical_allreduce
(module, config key, distributed test) so the name reflects both levels
it implements: LRAB intra-SIP (local reduce to center root + broadcast)
and the hierarchical inter-SIP topology exchange (ring/torus/mesh).
ADR-0032 slug kept as the stable decision id; pure rename, no logic change.
Also in this batch:
- ADR-0032 (EN+KO): document the shipped center-root bidirectional reduce
(doc was stale corner-root); annotate ccl.yaml root_cube as a placeholder.
- Rename allreduce + pe2pe latency plots to descriptive, title-matching
filenames and retitle the in-plot headings; drop overview/overview_log.
- Point the PPTX image refs at the new plot names.
Doc + derived-artifact + rename only; no simulation behavior changed.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The unified ccl_allreduce bench previously carried two execution models
in one worker with ``if world_size == n_sips:`` branching:
- TP mode (rank = SIP, ADR-0024/0027): proper ProcessGroup semantics.
- Legacy rank = PE mode: single-driver worker allocating one big tensor
distributed across all PEs via _derive_dp, with kernel-level SPMD via
program_id.
The second model is unnecessary — intra-SIP PE-level collectives are
expressed inside the kernel (tl.send/tl.recv with program_id, IPCQ) and
do not need a host-side ProcessGroup. Removing it lets the bench be a
clean reference implementation of the TP launcher.
benches/ccl_allreduce.py:
- Config resolved once in run() via _resolve_cfg -> _BenchCfg dataclass.
- rank != n_sips now raises RuntimeError explicitly.
- _worker / _allocate_rank_tile / _init_with_rank_value / _report each
have one concern; duplicated init + verification paths collapsed.
- _derive_dp and the second verify+print block deleted.
- 166 lines -> 91 lines.
ccl.yaml:
- mesh_allreduce_4 (world_size: 4) and tree_allreduce_7 (world_size: 7)
algorithm entries removed (rank = PE only).
- Algorithm kernel files (kernbench.ccl.algorithms.mesh_allreduce,
tree_allreduce) kept as-is for direct-dispatch future use.
tests/test_ccl_allreduce_matrix.py:
- Matrix shrinks from 7 cases to 3: ring × {tcm, hbm, sram} at ws =
topology SIP count (= 2). mesh_2x2, tree_binary_7, ring_multi_cube,
and the three ring_*_8 cases removed.
tests/test_ccl_performance.py:
- _run_8rank renamed to _run_ring; world_size: 8 override dropped; now
exercises rank = SIP ring all-reduce.
tests/test_mp_spawn.py, tests/test_ccl_ddp_launcher.py:
- Monkeypatch target updated from bench.worker to bench._worker
(signature now takes BenchCfg instead of (rank, world_size)).
555 passed, 1 intentional skip. Tests that directly call
install_ipcq(world_size_override=N) for kernel-level sanity
(test_ccl_hello_world_guide, test_recv_copy_to_dst, test_tl_recv_async,
test_ccl_deadlock_detection) are unchanged — they never went through
the bench and still exercise the kernel-only path.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Tensor.__setitem__ / __getitem__:
- Shard-aligned slice assignment and read on deployed tensors.
- Scalar broadcast and numpy array assignment supported.
- Cross-shard slices raise NotImplementedError (use copy_ for that).
- 3 new tests: single-PE, multi-PE, cross-shard error case.
Hierarchical all-reduce kernel (src/kernbench/ccl/algorithms/):
- 3-level reduce: intra-cube (E/W) → inter-cube (N/S) → inter-SIP (parent).
- Bidirectional ring reduce at each level: ceil((N-1)/2) rounds.
Left half sends via dir_dec, right half via dir_inc (wrap).
Representative receives from both sides.
- Chain broadcast for reverse path: cube 0 PE 0 → all PE 0s → all PEs.
- Registered in ccl.yaml as "hierarchical_allreduce" with topology: none
(neighbors() override builds the full 3-level neighbor map).
- kernel_args derives pes_per_cube/cubes_per_sip/num_sips from world_size.
- Mock-verified at 8/16/32/64/128 ranks.
Mock runtime fixes:
- Direction pairing: explicit N↔S, E↔W, parent↔parent instead of
"first matching reverse". Fixes 2-element rings where N and S both
point to the same peer.
- Deadlock detection: send-counter based (not just queue-depth-total)
to catch chain reductions where send+recv pairs net to zero.
- Multi-cube program_id: pes_per_cube parameter enables
program_id(axis=0) = PE within cube, program_id(axis=1) = cube id.
Legacy single-cube tests unaffected (default = world_size).
504 tests pass in 12s.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
mukesh
ywkang