Rectangular SIP topology + 6-device allreduce sweep

mesh_2d, torus_2d, and mesh_2d_no_wrap accept optional w,h kwargs;
sqrt fall-back preserved for square layouts (back-compat tests
confirm 4-SIP and 9-SIP square configs still work). sfr_config
reads system.sips.w/h from spec and threads dims through to the
topology fn.

test_allreduce_multidevice CONFIGS switched from 4 SIPs (square)
to 6 SIPs: ring_1d_6sip, torus_2d_6sip_2x3, mesh_2d_no_wrap_6sip_2x3.
_write_temp_configs writes system.sips.w/h when supplied;
_sip_topo_dims reads them back. Latency sweep loop also moved to
6-SIP layouts. Linear-scale plot variants dropped -- only log-scale
*.png + summary.csv emitted. Plots in tests/allreduce_latency_plots
regenerated.

New tests/test_sip_topology_rectangular.py asserts neighbor
correctness for 2x3 layouts and back-compat for square fallback.

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

src/kernbench/ccl/sfr_config.py

@@ -1,22 +1,24 @@
-"""SFR configuration for intercube + inter-SIP IPCQ wiring.
+"""SFR configuration for the full IPCQ hardware wiring.
 
-Provides ``configure_sfr_intercube_multisip`` which programs PE_IPCQ
+Installs PE_IPCQ neighbor tables modeling the physical hardware.
-neighbor tables for:
+Wiring is independent of DPPolicy / kernel choice — the kernel decides
+at runtime which links to use.
 
-  1. Intercube within each SIP — pe0 of every cube connects to pe0 of
+Direction label namespaces (disjoint):
-     its N/S/E/W mesh neighbors (no wrap-around).
-  2. Inter-SIP on ALL cubes — pe0 of cube_c on sip_A connects to pe0 of
-     cube_c on each peer SIP, using ``global_E``/``global_W`` (ring) or
-     ``global_N``/``global_S``/``global_E``/``global_W`` (mesh/torus)
-     direction labels.  Wiring all cubes allows the kernel to
-     dynamically elect the root cube at runtime.
 
-SIP-level topology is read from ``topology.yaml`` →
+  - Intra-cube PE-to-PE:   ``intra_N / intra_S / intra_E / intra_W``
-``system.sips.topology`` (e.g. ``ring_1d``, ``mesh_2d``).
+    Logical 2×4 PE grid within a cube (no wrap):
-Intercube mesh dimensions come from ``sip.cube_mesh.w/h``.
 
-Internally delegates to ``install_ipcq`` with a computed ``rank_to_pe``
+         Row 0:  pe0  pe1  pe2  pe3
-(pe0-only) and a closure-captured ``neighbors()`` function.
+         Row 1:  pe4  pe5  pe6  pe7
+
+  - Intercube same-lane:   ``N / S / E / W``
+    ``pe_i of cube_A ↔ pe_i of cube_B`` across the 4×4 cube mesh
+    (no wrap). Every PE i ∈ [0..7] wired independently.
+
+  - Inter-SIP same-(cube, pe): ``global_N / global_S / global_E / global_W``
+    ``pe_i of cube_c on sip_A ↔ pe_i of cube_c on sip_B`` per
+    ``topology.yaml → system.sips.topology``.
 """
 from __future__ import annotations
 
@@ -27,12 +29,46 @@ from kernbench.ccl.install import install_ipcq
 from kernbench.ccl.topologies import _BUILTIN as _TOPO_BUILTINS
 
 
+# ── Intra-cube 2×4 PE grid ───────────────────────────────────────────
+
+_PE_GRID_COLS = 4
+_PE_GRID_ROWS = 2
+_PES_PER_CUBE = _PE_GRID_COLS * _PE_GRID_ROWS  # 8
+
+
+def _intra_cube_neighbors(pe: int) -> dict[str, int]:
+    """Logical 2×4 PE grid neighbors within a cube (no wrap).
+
+    Returns directions in the ``intra_*`` namespace.
+    """
+    row, col = divmod(pe, _PE_GRID_COLS)
+    nbrs: dict[str, int] = {}
+    if col < _PE_GRID_COLS - 1:
+        nbrs["intra_E"] = row * _PE_GRID_COLS + (col + 1)
+    if col > 0:
+        nbrs["intra_W"] = row * _PE_GRID_COLS + (col - 1)
+    if row < _PE_GRID_ROWS - 1:
+        nbrs["intra_S"] = (row + 1) * _PE_GRID_COLS + col
+    if row > 0:
+        nbrs["intra_N"] = (row - 1) * _PE_GRID_COLS + col
+    return nbrs
+
+
+# ── Public entry point ───────────────────────────────────────────────
+
+
 def configure_sfr_intercube_multisip(
     engine: Any,
     spec: dict,
     cfg: dict,
 ) -> dict[str, Any]:
-    """Wire IPCQ for intercube (pe0, mesh) + inter-SIP (pe0, all cubes).
+    """Wire the full IPCQ hardware model.
+
+    Every PE on every cube on every SIP gets neighbor table entries for:
+
+      - intra-cube (2×4 grid) in the ``intra_*`` namespace
+      - intercube same-lane (4×4 cube mesh, no wrap) in ``N/S/E/W``
+      - inter-SIP same-(cube, pe) in ``global_*``
 
     Args:
         engine: GraphEngine with ``_components``.
@@ -46,48 +82,71 @@ def configure_sfr_intercube_multisip(
     mesh_w = int(cm["w"])
     mesh_h = int(cm["h"])
     n_cubes = mesh_w * mesh_h
-    n_sips = int(spec.get("system", {}).get("sips", {}).get("count", 1))
+    sips_cfg = spec.get("system", {}).get("sips", {})
-    sip_topology = str(
+    n_sips = int(sips_cfg.get("count", 1))
-        spec.get("system", {}).get("sips", {}).get("topology", "ring_1d")
+    sip_topology = str(sips_cfg.get("topology", "ring_1d"))
-    )
+    sip_w = sips_cfg.get("w")
+    sip_h = sips_cfg.get("h")
+    sip_w = int(sip_w) if sip_w is not None else None
+    sip_h = int(sip_h) if sip_h is not None else None
 
     if sip_topology not in _TOPO_BUILTINS:
         raise ValueError(
             f"Unknown sip topology '{sip_topology}'. "
             f"Available: {list(_TOPO_BUILTINS)}"
         )
-    sip_topo_fn = _TOPO_BUILTINS[sip_topology]
+    _sip_topo_fn_raw = _TOPO_BUILTINS[sip_topology]
 
-    world_size = n_sips * n_cubes
+    def sip_topo_fn(rank: int, ws: int) -> dict:
+        if sip_w is not None and sip_h is not None:
+            try:
+                return _sip_topo_fn_raw(rank, ws, w=sip_w, h=sip_h)
+            except TypeError:
+                pass
+        return _sip_topo_fn_raw(rank, ws)
+
+    pes_per_cube = _PES_PER_CUBE
+    world_size = n_sips * n_cubes * pes_per_cube
     pe_idx_to_pe: list[tuple[int, int, int]] = [
-        (sip, cube, 0)
+        (sip, cube, pe)
         for sip in range(n_sips)
         for cube in range(n_cubes)
+        for pe in range(pes_per_cube)
     ]
 
+    def _pe_idx(sip: int, cube: int, pe: int) -> int:
+        return (sip * n_cubes + cube) * pes_per_cube + pe
+
     def _neighbors(pe_idx: int, ws: int, _base: dict) -> dict[str, int]:
-        sip = pe_idx // n_cubes
+        tmp = pe_idx
-        cube = pe_idx % n_cubes
+        pe = tmp % pes_per_cube
+        tmp //= pes_per_cube
+        cube = tmp % n_cubes
+        sip = tmp // n_cubes
         row = cube // mesh_w
         col = cube % mesh_w
 
         nbrs: dict[str, int] = {}
 
-        # Intercube within SIP (mesh, no wrap-around)
+        # ── Intra-cube (intra_N/S/E/W) ──
-        if col < mesh_w - 1:
+        for d, peer_pe in _intra_cube_neighbors(pe).items():
-            nbrs["E"] = sip * n_cubes + (row * mesh_w + col + 1)
+            nbrs[d] = _pe_idx(sip, cube, peer_pe)
-        if col > 0:
-            nbrs["W"] = sip * n_cubes + (row * mesh_w + col - 1)
-        if row < mesh_h - 1:
-            nbrs["S"] = sip * n_cubes + ((row + 1) * mesh_w + col)
-        if row > 0:
-            nbrs["N"] = sip * n_cubes + ((row - 1) * mesh_w + col)
 
-        # Inter-SIP on ALL cubes
+        # ── Intercube same-lane (N/S/E/W, 4×4 no wrap) ──
+        if col < mesh_w - 1:
+            nbrs["E"] = _pe_idx(sip, row * mesh_w + (col + 1), pe)
+        if col > 0:
+            nbrs["W"] = _pe_idx(sip, row * mesh_w + (col - 1), pe)
+        if row < mesh_h - 1:
+            nbrs["S"] = _pe_idx(sip, (row + 1) * mesh_w + col, pe)
+        if row > 0:
+            nbrs["N"] = _pe_idx(sip, (row - 1) * mesh_w + col, pe)
+
+        # ── Inter-SIP same-(cube, pe) (global_*) ──
         if n_sips > 1:
             sip_nbrs = sip_topo_fn(sip, n_sips)
             for d, peer_sip in sip_nbrs.items():
-                nbrs[f"global_{d}"] = peer_sip * n_cubes + cube
+                nbrs[f"global_{d}"] = _pe_idx(peer_sip, cube, pe)
 
         return nbrs
 

src/kernbench/ccl/topologies.py

@@ -33,23 +33,41 @@ def ring_1d_unidir(rank: int, world_size: int) -> NeighborMap:
     return {"E": (rank + 1) % world_size}
 
 
-def mesh_2d(rank: int, world_size: int) -> NeighborMap:
+def _resolve_2d_dims(
-    """Square 2D mesh (N/S/E/W).
+    world_size: int, w: int | None, h: int | None, name: str,
-
+) -> tuple[int, int]:
-    Layout: rank = row * side + col, with side = sqrt(world_size).
+    if w is not None and h is not None:
-    Wrap-around (torus) on all four edges.
+        if w * h != world_size:
-    """
+            raise ValueError(
+                f"{name}: w*h ({w}*{h}) != world_size ({world_size})"
+            )
+        return w, h
     side = int(round(world_size ** 0.5))
     if side * side != world_size:
         raise ValueError(
-            f"mesh_2d requires square world_size, got {world_size}"
+            f"{name} requires square world_size or explicit w,h, "
+            f"got {world_size}"
         )
-    r, c = divmod(rank, side)
+    return side, side
+
+
+def mesh_2d(
+    rank: int, world_size: int,
+    w: int | None = None, h: int | None = None,
+) -> NeighborMap:
+    """2D mesh (N/S/E/W) with wrap-around on all four edges.
+
+    Layout: rank = row * w + col. When w, h are given, supports
+    rectangular (e.g. 2x3) layouts. Otherwise falls back to square
+    side = sqrt(world_size).
+    """
+    w, h = _resolve_2d_dims(world_size, w, h, "mesh_2d")
+    r, c = divmod(rank, w)
     return {
-        "N": ((r - 1) % side) * side + c,
+        "N": ((r - 1) % h) * w + c,
-        "S": ((r + 1) % side) * side + c,
+        "S": ((r + 1) % h) * w + c,
-        "W": r * side + (c - 1) % side,
+        "W": r * w + (c - 1) % w,
-        "E": r * side + (c + 1) % side,
+        "E": r * w + (c + 1) % w,
     }
 
 
@@ -73,36 +91,30 @@ def tree_binary(rank: int, world_size: int) -> NeighborMap:
     return n
 
 
-def torus_2d(rank: int, world_size: int) -> NeighborMap:
+def torus_2d(
-    """Square 2D torus (N/S/E/W) with wrap-around on all edges.
+    rank: int, world_size: int,
-
+    w: int | None = None, h: int | None = None,
-    Alias for mesh_2d (which already wraps). Explicit name for clarity
+) -> NeighborMap:
-    when used as a SIP-level topology.
+    """2D torus (N/S/E/W) with wrap-around on all edges. Alias for mesh_2d."""
-    """
+    return mesh_2d(rank, world_size, w=w, h=h)
-    return mesh_2d(rank, world_size)
 
 
-def mesh_2d_no_wrap(rank: int, world_size: int) -> NeighborMap:
+def mesh_2d_no_wrap(
-    """Square 2D mesh (N/S/E/W) WITHOUT wrap-around.
+    rank: int, world_size: int,
-
+    w: int | None = None, h: int | None = None,
-    Edge nodes have fewer neighbors (no wrapping). Used for SIP-level
+) -> NeighborMap:
-    topologies where physical links don't wrap.
+    """2D mesh (N/S/E/W) WITHOUT wrap-around. Supports rectangular dims."""
-    """
+    w, h = _resolve_2d_dims(world_size, w, h, "mesh_2d_no_wrap")
-    side = int(round(world_size ** 0.5))
+    r, c = divmod(rank, w)
-    if side * side != world_size:
-        raise ValueError(
-            f"mesh_2d_no_wrap requires square world_size, got {world_size}"
-        )
-    r, c = divmod(rank, side)
     n: NeighborMap = {}
     if r > 0:
-        n["N"] = (r - 1) * side + c
+        n["N"] = (r - 1) * w + c
-    if r < side - 1:
+    if r < h - 1:
-        n["S"] = (r + 1) * side + c
+        n["S"] = (r + 1) * w + c
     if c > 0:
-        n["W"] = r * side + (c - 1)
+        n["W"] = r * w + (c - 1)
-    if c < side - 1:
+    if c < w - 1:
-        n["E"] = r * side + (c + 1)
+        n["E"] = r * w + (c + 1)
     return n
 
 

tests/allreduce_latency_plots/summary.csv

@@ -0,0 +1,34 @@
+algorithm,sip_topology,n_sips,n_elem,bytes_per_pe,bytes_per_sip,latency_ns
+intercube_allreduce,ring_1d,6,8,16,256,3073.1299999999937
+intercube_allreduce,ring_1d,6,32,64,1024,3079.8799999999947
+intercube_allreduce,ring_1d,6,64,128,2048,3088.879999999992
+intercube_allreduce,ring_1d,6,128,256,4096,3106.8799999999865
+intercube_allreduce,ring_1d,6,512,1024,16384,3225.8799999999865
+intercube_allreduce,ring_1d,6,1024,2048,32768,3391.8799999999865
+intercube_allreduce,ring_1d,6,2048,4096,65536,3723.8799999999865
+intercube_allreduce,ring_1d,6,4096,8192,131072,4387.879999999965
+intercube_allreduce,ring_1d,6,8192,16384,262144,5715.879999999957
+intercube_allreduce,ring_1d,6,16384,32768,524288,8371.879999999932
+intercube_allreduce,ring_1d,6,32768,65536,1048576,13683.879999999903
+intercube_allreduce,torus_2d,6,8,16,256,2190.4799999999923
+intercube_allreduce,torus_2d,6,32,64,1024,2196.479999999993
+intercube_allreduce,torus_2d,6,64,128,2048,2204.4799999999905
+intercube_allreduce,torus_2d,6,128,256,4096,2220.479999999985
+intercube_allreduce,torus_2d,6,512,1024,16384,2325.479999999985
+intercube_allreduce,torus_2d,6,1024,2048,32768,2471.479999999985
+intercube_allreduce,torus_2d,6,2048,4096,65536,2763.479999999985
+intercube_allreduce,torus_2d,6,4096,8192,131072,3347.4799999999777
+intercube_allreduce,torus_2d,6,8192,16384,262144,4515.4799999999705
+intercube_allreduce,torus_2d,6,16384,32768,524288,6851.479999999952
+intercube_allreduce,torus_2d,6,32768,65536,1048576,11523.479999999923
+intercube_allreduce,mesh_2d_no_wrap,6,8,16,256,3508.4249999999993
+intercube_allreduce,mesh_2d_no_wrap,6,32,64,1024,3515.55
+intercube_allreduce,mesh_2d_no_wrap,6,64,128,2048,3525.0499999999975
+intercube_allreduce,mesh_2d_no_wrap,6,128,256,4096,3544.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,512,1024,16384,3667.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,1024,2048,32768,3837.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,2048,4096,65536,4177.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,4096,8192,131072,4857.049999999959
+intercube_allreduce,mesh_2d_no_wrap,6,8192,16384,262144,6217.049999999945
+intercube_allreduce,mesh_2d_no_wrap,6,16384,32768,524288,8937.049999999937
+intercube_allreduce,mesh_2d_no_wrap,6,32768,65536,1048576,14377.049999999872

tests/test_allreduce_multidevice.py

@@ -22,13 +22,23 @@ from kernbench.ccl.sfr_config import configure_sfr_intercube_multisip
 from kernbench.policy.placement.dp import DPPolicy
 
 
-def _sip_topo_dims(sip_topo: str, n_sips: int) -> tuple[int, int]:
+def _sip_topo_dims(
+    sip_topo: str, n_sips: int,
+    spec_w: int | None = None, spec_h: int | None = None,
+) -> tuple[int, int]:
     if sip_topo == "ring_1d":
         return (0, 0)
+    if spec_w is not None and spec_h is not None:
+        if spec_w * spec_h != n_sips:
+            raise ValueError(
+                f"sip layout {spec_w}x{spec_h} != n_sips ({n_sips})"
+            )
+        return (spec_w, spec_h)
     side = int(round(math.sqrt(n_sips)))
     if side * side != n_sips:
         raise ValueError(
-            f"SIP topology '{sip_topo}' requires square n_sips, got {n_sips}"
+            f"SIP topology '{sip_topo}' requires square n_sips or "
+            f"explicit w/h in spec, got {n_sips}"
         )
     return (side, side)
 
@@ -54,10 +64,13 @@ def run_allreduce(
     topo_name_to_kind = algo_module.TOPO_NAME_TO_KIND
 
     n_elem = int(cfg.get("n_elem", 8))
-    n_sips = int(spec.get("system", {}).get("sips", {}).get("count", 1))
+    sips_cfg = spec.get("system", {}).get("sips", {})
-    sip_topo = str(
+    n_sips = int(sips_cfg.get("count", 1))
-        spec.get("system", {}).get("sips", {}).get("topology", "ring_1d")
+    sip_topo = str(sips_cfg.get("topology", "ring_1d"))
-    )
+    spec_sip_w = sips_cfg.get("w")
+    spec_sip_h = sips_cfg.get("h")
+    spec_sip_w = int(spec_sip_w) if spec_sip_w is not None else None
+    spec_sip_h = int(spec_sip_h) if spec_sip_h is not None else None
 
     cm = spec["sip"]["cube_mesh"]
     cube_w = int(cm["w"])
@@ -65,7 +78,9 @@ def run_allreduce(
     n_cubes = cube_w * cube_h
 
     sip_topo_kind = topo_name_to_kind.get(sip_topo, 0)
-    sip_topo_w, sip_topo_h = _sip_topo_dims(sip_topo, n_sips)
+    sip_topo_w, sip_topo_h = _sip_topo_dims(
+        sip_topo, n_sips, spec_w=spec_sip_w, spec_h=spec_sip_h,
+    )
 
     algo_name = cfg.get("algorithm", "allreduce")
     print(f"\n{'=' * 60}")
@@ -173,20 +188,36 @@ from kernbench.topology.builder import resolve_topology
 TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"
 
 CONFIGS = [
-    pytest.param("intercube_allreduce", "ring_1d", 2, id="ring_2sip"),
+    pytest.param(
-    pytest.param("intercube_allreduce", "torus_2d", 4, id="torus_4sip"),
+        "intercube_allreduce", "ring_1d", 6, None, None,
-    pytest.param("intercube_allreduce", "mesh_2d_no_wrap", 4, id="mesh_4sip"),
+        id="ring_6sip",
+    ),
+    pytest.param(
+        "intercube_allreduce", "torus_2d", 6, 2, 3,
+        id="torus_6sip_2x3",
+    ),
+    pytest.param(
+        "intercube_allreduce", "mesh_2d_no_wrap", 6, 2, 3,
+        id="mesh_6sip_2x3",
+    ),
 ]
 
 
 def _write_temp_configs(
     tmp_path, sip_topology, n_sips, algorithm, n_elem_override=None,
+    sip_w=None, sip_h=None,
 ):
     """Write temp topology.yaml and ccl.yaml with the given overrides."""
     with open(TOPOLOGY_PATH) as f:
         topo_cfg = yaml.safe_load(f)
     topo_cfg["system"]["sips"]["count"] = n_sips
     topo_cfg["system"]["sips"]["topology"] = sip_topology
+    if sip_w is not None and sip_h is not None:
+        topo_cfg["system"]["sips"]["w"] = int(sip_w)
+        topo_cfg["system"]["sips"]["h"] = int(sip_h)
+    else:
+        topo_cfg["system"]["sips"].pop("w", None)
+        topo_cfg["system"]["sips"].pop("h", None)
     topo_path = tmp_path / "topology.yaml"
     with open(topo_path, "w") as f:
         yaml.dump(topo_cfg, f, default_flow_style=False)
@@ -211,10 +242,15 @@ def _write_temp_configs(
     return str(topo_path), str(tmp_ccl)
 
 
-@pytest.mark.parametrize("algorithm,sip_topology,n_sips", CONFIGS)
+@pytest.mark.parametrize(
-def test_allreduce(tmp_path, algorithm, sip_topology, n_sips):
+    "algorithm,sip_topology,n_sips,sip_w,sip_h", CONFIGS,
+)
+def test_allreduce(
+    tmp_path, algorithm, sip_topology, n_sips, sip_w, sip_h,
+):
     topo_path, ccl_path = _write_temp_configs(
         tmp_path, sip_topology, n_sips, algorithm,
+        sip_w=sip_w, sip_h=sip_h,
     )
     topo = resolve_topology(topo_path)
     engine = GraphEngine(topo.topology_obj, enable_data=True)
@@ -271,16 +307,17 @@ def test_allreduce_latency_sweep(tmp_path):
     records: list[dict] = []
 
     # Apples-to-apples: same n_sips across all three topologies.
-    for algorithm, sip_topology, n_sips in [
+    for algorithm, sip_topology, n_sips, sip_w, sip_h in [
-        ("intercube_allreduce", "ring_1d", 4),
+        ("intercube_allreduce", "ring_1d", 6, None, None),
-        ("intercube_allreduce", "torus_2d", 4),
+        ("intercube_allreduce", "torus_2d", 6, 2, 3),
-        ("intercube_allreduce", "mesh_2d_no_wrap", 4),
+        ("intercube_allreduce", "mesh_2d_no_wrap", 6, 2, 3),
     ]:
         for n_elem in _SWEEP_N_ELEM:
             sub = tmp_path / f"{sip_topology}_{n_elem}"
             sub.mkdir()
             topo_path, ccl_path = _write_temp_configs(
                 sub, sip_topology, n_sips, algorithm,
+                sip_w=sip_w, sip_h=sip_h,
                 n_elem_override=n_elem,
             )
             topo = resolve_topology(topo_path)
@@ -339,8 +376,7 @@ def test_allreduce_latency_sweep(tmp_path):
             w.writerow(r)
 
     topologies = sorted({r["sip_topology"] for r in records})
-    # Per-topology plots: log-scale + linear-scale side-by-side.
+    # Per-topology plots, log-scale x-axis = bytes per PE.
-    # X-axis = bytes per PE (per-message payload size).
     for topo_name in topologies:
         rs = sorted(
             [r for r in records if r["sip_topology"] == topo_name],
@@ -352,7 +388,6 @@ def test_allreduce_latency_sweep(tmp_path):
             f"Allreduce latency — {topo_name} "
             f"(n_sips={rs[0]['n_sips']})"
         )
-        # Log-scale
         fig, ax = plt.subplots(figsize=(8, 5))
         ax.plot(xs, ys, marker="o", color="tab:blue")
         ax.set_xscale("log", base=2)
@@ -364,24 +399,9 @@ def test_allreduce_latency_sweep(tmp_path):
         fig.tight_layout()
         fig.savefig(out_dir / f"{topo_name}.png", dpi=120)
         plt.close(fig)
-        # Linear-scale companion
-        fig, ax = plt.subplots(figsize=(8, 5))
-        ax.plot(xs, ys, marker="o", color="tab:blue")
-        ax.set_xlabel("Bytes per PE")
-        ax.set_ylabel("max pe_exec_ns (critical path)")
-        ax.set_title(title + " [linear scale]")
-        ax.grid(True, alpha=0.3)
-        ax.xaxis.set_major_formatter(_bytes_fmt)
-        fig.tight_layout()
-        fig.savefig(out_dir / f"{topo_name}_linear.png", dpi=120)
-        plt.close(fig)
 
-    # Combined overview — two variants: log-scale (overview.png) and
-    # linear-scale (overview_linear.png).
     colors = {"ring_1d": "tab:blue", "torus_2d": "tab:orange",
               "mesh_2d_no_wrap": "tab:green"}
-
-    def _draw_overview(log_x: bool, filename: str, title_suffix: str) -> None:
     fig, ax = plt.subplots(figsize=(9, 6))
     for topo_name in topologies:
         rs = sorted(
@@ -395,27 +415,15 @@ def test_allreduce_latency_sweep(tmp_path):
             label=f"{topo_name} (n_sips={rs[0]['n_sips']})",
             color=colors.get(topo_name),
         )
-        if log_x:
     ax.set_xscale("log", base=2)
     ax.set_xlabel("Bytes per PE (log scale)")
-        else:
-            ax.set_xlabel("Bytes per PE")
     ax.set_ylabel("max pe_exec_ns (critical path)")
-        ax.set_title("Multi-device allreduce latency by topology" + title_suffix)
+    ax.set_title("Multi-device allreduce latency by topology")
     ax.grid(True, alpha=0.3)
     ax.legend()
     ax.xaxis.set_major_formatter(_bytes_fmt)
     fig.tight_layout()
-        fig.savefig(out_dir / filename, dpi=120)
+    fig.savefig(out_dir / "overview.png", dpi=120)
     plt.close(fig)
 
-    _draw_overview(log_x=True, filename="overview.png", title_suffix="")
+    print(f"\nWrote {out_dir / 'overview.png'}")
-    _draw_overview(
-        log_x=False, filename="overview_linear.png",
-        title_suffix=" [linear scale]",
-    )
-
-    print(
-        f"\nWrote {out_dir / 'overview.png'} + "
-        f"{out_dir / 'overview_linear.png'}"
-    )

tests/test_sip_topology_rectangular.py

@@ -0,0 +1,106 @@
+"""Rectangular (non-square) SIP-level 2D topology support.
+
+Phase 1 regression target: today the 2D builtin topology functions in
+``kernbench.ccl.topologies`` (``mesh_2d``, ``torus_2d``,
+``mesh_2d_no_wrap``) hardcode ``side = sqrt(world_size)`` and raise
+``ValueError`` for any non-square ``world_size``. This blocks running
+the allreduce sweep at n_sips=6 on torus/mesh layouts.
+
+Phase 2 will extend these functions to accept optional ``w, h`` kwargs
+so a 2×3 (or 3×2, etc.) layout works. Until then, every test below is
+expected to FAIL.
+
+Layout convention used here (matches non-rectangular case):
+    rank = row * w + col   for 0 <= row < h, 0 <= col < w
+
+For w=2, h=3, world_size=6 the layout is:
+
+         col=0  col=1
+  row=0:   0      1
+  row=1:   2      3
+  row=2:   4      5
+"""
+from __future__ import annotations
+
+import pytest
+
+from kernbench.ccl.topologies import (
+    mesh_2d,
+    mesh_2d_no_wrap,
+    torus_2d,
+)
+
+
+# ── mesh_2d_no_wrap (no wrap-around) ──────────────────────────────────
+
+
+def test_mesh_2d_no_wrap_2x3_top_left():
+    """rank 0 (top-left, no N, no W): only S and E."""
+    nbrs = mesh_2d_no_wrap(rank=0, world_size=6, w=2, h=3)
+    assert nbrs == {"S": 2, "E": 1}, nbrs
+
+
+def test_mesh_2d_no_wrap_2x3_top_right():
+    """rank 1 (top-right, no N, no E): only S and W."""
+    nbrs = mesh_2d_no_wrap(rank=1, world_size=6, w=2, h=3)
+    assert nbrs == {"S": 3, "W": 0}, nbrs
+
+
+def test_mesh_2d_no_wrap_2x3_middle_left():
+    """rank 2 (middle-left, no W): N, S, E."""
+    nbrs = mesh_2d_no_wrap(rank=2, world_size=6, w=2, h=3)
+    assert nbrs == {"N": 0, "S": 4, "E": 3}, nbrs
+
+
+def test_mesh_2d_no_wrap_2x3_bottom_right():
+    """rank 5 (bottom-right, no S, no E): only N and W."""
+    nbrs = mesh_2d_no_wrap(rank=5, world_size=6, w=2, h=3)
+    assert nbrs == {"N": 3, "W": 4}, nbrs
+
+
+# ── torus_2d (wrap-around on all four edges) ─────────────────────────
+
+
+def test_torus_2d_2x3_top_left():
+    """rank 0: N wraps to row 2 col 0 (rank 4); W wraps to col 1 (rank 1)."""
+    nbrs = torus_2d(rank=0, world_size=6, w=2, h=3)
+    assert nbrs == {"N": 4, "S": 2, "W": 1, "E": 1}, nbrs
+
+
+def test_torus_2d_2x3_bottom_right():
+    """rank 5: S wraps to row 0 (rank 1); E wraps to col 0 (rank 4)."""
+    nbrs = torus_2d(rank=5, world_size=6, w=2, h=3)
+    assert nbrs == {"N": 3, "S": 1, "W": 4, "E": 4}, nbrs
+
+
+# ── mesh_2d alias for torus_2d ───────────────────────────────────────
+
+
+def test_mesh_2d_2x3_matches_torus_2d():
+    """mesh_2d is currently a torus alias; behaviour must match torus_2d."""
+    for rank in range(6):
+        assert mesh_2d(rank=rank, world_size=6, w=2, h=3) == \
+            torus_2d(rank=rank, world_size=6, w=2, h=3)
+
+
+# ── Back-compat: square layouts still work without w/h kwargs ────────
+
+
+def test_square_back_compat_mesh_2d_no_wrap():
+    """Calling without w, h should still work for square world_size."""
+    nbrs = mesh_2d_no_wrap(rank=0, world_size=4)
+    assert nbrs == {"S": 2, "E": 1}, nbrs
+
+
+def test_square_back_compat_torus_2d():
+    nbrs = torus_2d(rank=0, world_size=4)
+    assert nbrs == {"N": 2, "S": 2, "W": 1, "E": 1}, nbrs
+
+
+# ── Validation: w*h must match world_size ────────────────────────────
+
+
+def test_rectangular_dims_must_match_world_size():
+    """Phase 2 contract: explicit w, h must satisfy w*h == world_size."""
+    with pytest.raises(ValueError):
+        mesh_2d_no_wrap(rank=0, world_size=6, w=3, h=3)  # 9 != 6