sccl: drive allreduce tests via torch.distributed; reorganize into tests/sccl/

Convert the multidevice allreduce correctness + latency/buffer-kind sweeps
to run through the real PyTorch-distributed path
(init_process_group(backend="ahbm") -> mp.spawn -> dist.all_reduce) instead
of direct ctx.launch, and reorganize the CCL/allreduce tests into a
tests/sccl/ package split one test per file.

Production change (required for the distributed path on non-square SIP grids):
- AhbmCCLBackend now reads explicit system.sips.w/h from the spec, with a
  square-only sqrt fallback that raises on ambiguity, instead of silently
  guessing round(sqrt(count)). This fixes the 2x3 / 3x2 torus + mesh cases,
  which previously resolved to a wrong 2x2 grid. Mirrors the test helper's
  _sip_topo_dims precedence (explicit w/h > square fallback > raise).

Test reorganization (tests/sccl/):
- _allreduce_helpers.py: shared plumbing (distributed driver, config writers,
  direct-launch run_allreduce parity reference, sweep/buffer-kind constants,
  plot aggregators, topology-diagram + FSIM-comparison emitters).
- test_allreduce_ring_torus_mesh.py: correctness across ring/torus/mesh.
- test_distributed_default_topology.py: full distributed path on topology.yaml.
- test_plot_latency_sweep.py / test_plot_buffer_kind_sweep.py: sweep rows.
- test_plot_topology_diagram.py / test_plot_comparison_fsim.py: plot emitters.
- test_intercube_root_center.py: moved in (ADR-0032 center-root latency guard).

Also:
- Move the FSIM comparison plot generator out of scripts/ into the sccl suite.
- Delete superseded test files (test_allreduce_multidevice,
  test_distributed_lrab_hierarchical_allreduce, test_allreduce_buffer_kind_sweep)
  and repoint conftest aggregators + the ipcq buffer-kind importers.
- Regenerate the allreduce_latency_plots derived artifacts from the full sweep.

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

tests/sccl/test_plot_buffer_kind_sweep.py

@@ -0,0 +1,66 @@
+"""Buffer-kind sweep (TCM / SRAM / HBM) on torus_2d 6 SIPs (3×2), distributed.
+
+Each parametrized case writes one JSON row; the conftest sessionfinish hook
+calls ``aggregate_buffer_kind_plot`` to emit the comparison PNG + csv. Pre
+slot-latency modeling the three lines overlap exactly (slot access is
+latency-free today).
+"""
+from __future__ import annotations
+
+import json
+
+import pytest
+import yaml
+
+from tests.sccl._allreduce_helpers import (
+    _BK_ROWS_DIR,
+    _ELEM_BYTES_F16,
+    _bk_params,
+    _crit_ns,
+    _run_distributed,
+    _write_temp_configs,
+)
+
+
+@pytest.mark.parametrize("buffer_kind,n_elem", _bk_params())
+def test_buffer_kind_allreduce_one(tmp_path, monkeypatch, buffer_kind, n_elem):
+    sub = tmp_path / f"{buffer_kind}_{n_elem}"
+    sub.mkdir()
+    topo_path, ccl_path = _write_temp_configs(
+        sub,
+        sip_topology="torus_2d",
+        n_sips=6,
+        algorithm="lrab_hierarchical_allreduce",
+        sip_w=3, sip_h=2,
+        n_elem_override=n_elem,
+    )
+    # Override buffer_kind in the temp ccl.yaml (read by the ahbm backend
+    # at init_process_group time via load_ccl_config()).
+    with open(ccl_path) as f:
+        ccl_cfg = yaml.safe_load(f)
+    ccl_cfg.setdefault("defaults", {})["buffer_kind"] = buffer_kind
+    ccl_cfg.setdefault("algorithms", {}).setdefault(
+        "lrab_hierarchical_allreduce", {},
+    )["buffer_kind"] = buffer_kind
+    with open(ccl_path, "w") as f:
+        yaml.dump(ccl_cfg, f, default_flow_style=False)
+
+    engine, _ = _run_distributed(
+        sub, monkeypatch, topo_path,
+        f"bk_sweep_{buffer_kind}_{n_elem}", n_elem,
+    )
+    crit_ns = _crit_ns(engine)
+
+    bytes_per_pe = n_elem * _ELEM_BYTES_F16
+    record = {
+        "buffer_kind": buffer_kind,
+        "sip_topology": "torus_2d",
+        "n_sips": 6,
+        "n_elem": n_elem,
+        "bytes_per_pe": bytes_per_pe,
+        "latency_ns": crit_ns,
+    }
+    _BK_ROWS_DIR.mkdir(parents=True, exist_ok=True)
+    row_path = _BK_ROWS_DIR / f"{buffer_kind}_{n_elem}.json"
+    with open(row_path, "w", encoding="utf-8") as f:
+        json.dump(record, f)