Add CPU BlockLayout2D: core ownership, halo pairs, blocked packing

Fixed-size 2D blocks, block-contiguous Q-major storage, explicit per-axis
periodicity; non-periodic exterior halo cells stay unpaired (NaN).
Provides owner/halo tables for a later periodic GPU consumer. Cut-link
mapping deliberately omitted until the BFL write policy is settled.
Tests: ownership, pair invariants, pack round trip, tagged pull vs dense.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
Claude
2026-10-15 02:30:40 +00:00
co-authored by Claude Opus 5.5
parent 3a7967f4cc
commit a64af5bece
2 changed files with 312 additions and 0 deletions
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"""CPU layout for fixed-size 2D blocks: core ownership, halo pairs and packing.
Dense arrays are Q-major (q, y, x) with cell y*nx+x, as in core/layout.cuh.
Blocked storage is block-contiguous and Q-major inside each block:
(nblocks, q, by+2*halo, bx+2*halo). Block b = jy*nbx + jx has core origin
(jy*by, jx*bx). Every dense cell, fluid or solid, has exactly one core owner.
A "block cell" id is b*L + c with L=(by+2h)*(bx+2h) and c the local row-major
cell; its population q lives at flat slot b*NQ*L + q*L + c. Halo pairs copy
all NQ populations from an owner core cell into another block's halo cell.
Periodicity is explicit per axis. Across a non-periodic exterior, halo cells
have no pair and stay invalid (NaN after packing): no wrap, no implied BC.
Preparation only: no CUDA, no boundary conditions, no refinement levels.
"""
from dataclasses import dataclass
from numbers import Integral
import numpy as np
NQ = 9
FACE, CORNER = 0, 1
def _readonly(values, dtype):
array = np.ascontiguousarray(values, dtype=dtype)
array.setflags(write=False)
return array
def _positive_int(value, name):
if isinstance(value, (bool, np.bool_)) or not isinstance(value, Integral) or value <= 0:
raise ValueError(f"{name} must be a positive integer")
return int(value)
@dataclass(frozen=True, eq=False)
class BlockLayout2D:
"""Fixed-size block partition of an (ny, nx) grid; construct with build().
``origins`` rows are (y0, x0) core origins. ``owner`` maps each dense cell
to its owning block cell id. ``halo_dst``/``halo_src`` are block cell ids
(destination halo cell, source owner core cell) sorted by destination;
``halo_kind`` marks FACE or CORNER pairs. Sources are never halo cells, so
one gather in any order fills every valid halo cell.
"""
shape: tuple[int, int]
block: tuple[int, int]
halo: int
periodic: tuple[bool, bool]
origins: np.ndarray
owner: np.ndarray
halo_dst: np.ndarray
halo_src: np.ndarray
halo_kind: np.ndarray
@classmethod
def build(cls, ny, nx, by, bx, *, halo=1, periodic=(True, True)) -> "BlockLayout2D":
"""``periodic`` is (periodic_x, periodic_y); block sizes must divide the grid."""
ny, nx, by, bx, halo = (_positive_int(v, n) for v, n in
((ny, "ny"), (nx, "nx"), (by, "by"), (bx, "bx"), (halo, "halo")))
if ny % by or nx % bx:
raise ValueError("block sizes must divide the grid")
if halo > min(by, bx):
raise ValueError("halo may not exceed the block size")
if len(periodic) != 2 or not all(isinstance(p, (bool, np.bool_)) for p in periodic):
raise ValueError("periodic must be two booleans (x, y)")
px, py = map(bool, periodic)
nby, nbx = ny // by, nx // bx
ly, lx = by + 2 * halo, bx + 2 * halo
cells = ly * lx
if nby * nbx * NQ * cells > np.iinfo(np.int64).max // 2:
raise ValueError("blocked storage exceeds 64-bit indexing")
jy, jx = np.divmod(np.arange(nby * nbx), nbx)
origins = np.stack([jy * by, jx * bx], axis=1)
gy, gx = np.mgrid[0:ny, 0:nx]
owner = ((gy // by) * nbx + gx // bx) * cells + (gy % by + halo) * lx + gx % bx + halo
# Halo cells of one block in local row-major order, then all blocks.
hy, hx = np.mgrid[0:ly, 0:lx]
out_y = (hy < halo) | (hy >= by + halo)
out_x = (hx < halo) | (hx >= bx + halo)
ring = out_y | out_x
hy, hx, kind = hy[ring], hx[ring], np.where(out_y[ring] & out_x[ring], CORNER, FACE)
dst, src, kinds = [], [], []
for b, (y0, x0) in enumerate(origins):
sy, sx = y0 + hy - halo, x0 + hx - halo
if py:
sy %= ny
if px:
sx %= nx
keep = (sy >= 0) & (sy < ny) & (sx >= 0) & (sx < nx)
dst.append(b * cells + hy[keep] * lx + hx[keep])
src.append(owner[sy[keep], sx[keep]])
kinds.append(kind[keep])
return cls((ny, nx), (by, bx), halo, (px, py),
_readonly(origins, np.int64), _readonly(owner, np.uint64),
_readonly(np.concatenate(dst), np.uint64),
_readonly(np.concatenate(src), np.uint64),
_readonly(np.concatenate(kinds), np.uint8))
@property
def nblocks(self) -> int:
return len(self.origins)
@property
def local_shape(self) -> tuple[int, int]:
return self.block[0] + 2 * self.halo, self.block[1] + 2 * self.halo
@property
def blocked_shape(self) -> tuple[int, int, int, int]:
return (self.nblocks, NQ, *self.local_shape)
def slot(self, block_cell, q):
"""Flat blocked population slot of block cell id(s) for direction q."""
cells = int(np.prod(self.local_shape))
b, c = np.divmod(np.asarray(block_cell, dtype=np.uint64), np.uint64(cells))
return (b * np.uint64(NQ) + np.asarray(q, dtype=np.uint64)) * np.uint64(cells) + c
def block_cell(self, block, y, x):
"""Address of in-grid cell (y, x) in ``block``'s own storage, core or halo.
Periodic axes resolve to the image inside the block's halo window.
Raises if the cell is not represented there or lies across an exterior.
"""
by, bx = self.block
ly, lx = self.local_shape
ny, nx = self.shape
y0, x0 = self.origins[block]
ry, rx = int(y) - int(y0) + self.halo, int(x) - int(x0) + self.halo
if self.periodic[1] and not 0 <= ry < ly:
ry = next((r for r in (ry - ny, ry + ny) if 0 <= r < ly), ry)
if self.periodic[0] and not 0 <= rx < lx:
rx = next((r for r in (rx - nx, rx + nx) if 0 <= r < lx), rx)
if not (0 <= ry < ly and 0 <= rx < lx and 0 <= y < ny and 0 <= x < nx):
raise ValueError("cell is not represented in this block's storage")
return int(block) * ly * lx + ry * lx + rx
def exchange(self, blocked) -> None:
"""Fill every valid halo cell in place from its owner's core."""
blocked = self._check_blocked(blocked)
flat = blocked.reshape(self.nblocks, NQ, -1)
cells = flat.shape[2]
db, dc = np.divmod(self.halo_dst.astype(np.intp), cells)
sb, sc = np.divmod(self.halo_src.astype(np.intp), cells)
flat[db, :, dc] = flat[sb, :, sc]
def to_blocked(self, dense):
"""Pack (NQ, ny, nx) floats; halo cells without a pair stay NaN."""
dense = np.asarray(dense)
if dense.shape != (NQ, *self.shape) or not np.issubdtype(dense.dtype, np.floating):
raise ValueError(f"expected floating (NQ, ny, nx) = {(NQ, *self.shape)}")
blocked = np.full(self.blocked_shape, np.nan, dtype=dense.dtype)
flat = blocked.reshape(self.nblocks, NQ, -1)
ob, oc = np.divmod(self.owner.ravel().astype(np.intp), flat.shape[2])
flat[ob, :, oc] = dense.reshape(NQ, -1).T
self.exchange(blocked)
return blocked
def to_dense(self, blocked):
"""Unpack owner cores only; halo contents are ignored."""
blocked = self._check_blocked(blocked)
flat = blocked.reshape(self.nblocks, NQ, -1)
ob, oc = np.divmod(self.owner.ravel().astype(np.intp), flat.shape[2])
return np.ascontiguousarray(flat[ob, :, oc].T).reshape(NQ, *self.shape)
def _check_blocked(self, blocked):
if not isinstance(blocked, np.ndarray) or blocked.shape != self.blocked_shape \
or not blocked.flags.c_contiguous:
raise ValueError(f"expected C-contiguous blocked array {self.blocked_shape}")
return blocked
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"""CPU block layout contracts: ownership, halo pairs, packing and tagged pull."""
import sys
import unittest
import numpy as np
from CelerisLab.lbm.blocks import CORNER, FACE, NQ, BlockLayout2D
from CelerisLab.lbm.descriptors import D2Q9_EX, D2Q9_EY
CASES = ( # (ny, nx, by, bx, halo)
(6, 8, 3, 4, 1), # 2x2 split
(6, 12, 3, 4, 1), # 2x3 split
(8, 8, 4, 4, 2), # wider halo
(4, 8, 4, 4, 1), # one block along y
)
PERIODIC = ((True, True), (False, False), (True, False), (False, True))
def tags(ny, nx):
"""Unique, exactly representable value per dense population slot."""
return np.arange(NQ * ny * nx, dtype=np.float64).reshape(NQ, ny, nx)
def dense_pull(a, periodic):
"""f[q](x) = a[q](x - c_q); NaN where a non-periodic exterior is crossed."""
px, py = periodic
_, ny, nx = a.shape
gy, gx = np.mgrid[0:ny, 0:nx]
out = np.empty_like(a)
for q in range(NQ):
sy, sx = gy - D2Q9_EY[q], gx - D2Q9_EX[q]
valid = ((py | ((sy >= 0) & (sy < ny))) & (px | ((sx >= 0) & (sx < nx))))
out[q] = np.where(valid, a[q, sy % ny, sx % nx], np.nan)
return out
def blocked_pull(layout, blocked):
"""Exchange, then pull every core cell from its own block storage only."""
layout.exchange(blocked)
out = np.full_like(blocked, np.nan)
(by, bx), h = layout.block, layout.halo
for q in range(NQ):
ey, ex = D2Q9_EY[q], D2Q9_EX[q]
out[:, q, h:h + by, h:h + bx] = blocked[:, q, h - ey:h - ey + by, h - ex:h - ex + bx]
return out
class BlockLayoutTests(unittest.TestCase):
def test_cpu_import_boundary(self):
self.assertFalse(any(name == "pycuda" or name.startswith("pycuda.") for name in sys.modules))
def test_origins_and_unique_core_ownership(self):
layout = BlockLayout2D.build(6, 8, 3, 4)
np.testing.assert_array_equal(layout.origins, [[0, 0], [0, 4], [3, 0], [3, 4]])
self.assertEqual(layout.blocked_shape, (4, NQ, 5, 6))
for ny, nx, by, bx, h in CASES:
layout = BlockLayout2D.build(ny, nx, by, bx, halo=h)
ly, lx = layout.local_shape
core = [b * ly * lx + (y + h) * lx + x + h
for b in range(layout.nblocks) for y in range(by) for x in range(bx)]
self.assertEqual(sorted(layout.owner.ravel().tolist()), sorted(core))
for y in range(ny):
for x in range(nx):
b = (y // by) * (nx // bx) + x // bx
self.assertEqual(layout.block_cell(b, y, x), layout.owner[y, x])
def test_halo_pairs_are_owner_core_to_unique_halo(self):
for ny, nx, by, bx, h in CASES:
for periodic in PERIODIC:
layout = BlockLayout2D.build(ny, nx, by, bx, halo=h, periodic=periodic)
core = set(layout.owner.ravel().tolist())
dst = layout.halo_dst.tolist()
self.assertEqual(dst, sorted(dst))
self.assertEqual(len(dst), len(set(dst)))
self.assertTrue(core.isdisjoint(dst))
self.assertTrue(set(layout.halo_src.tolist()) <= core)
self.assertTrue(set(layout.halo_kind.tolist()) <= {FACE, CORNER})
full = BlockLayout2D.build(6, 8, 3, 4)
per_block = np.bincount(full.halo_kind, minlength=2) // full.nblocks
np.testing.assert_array_equal(per_block, [2 * (3 + 4), 4])
closed = BlockLayout2D.build(6, 8, 3, 4, periodic=(False, False))
# Each 2x2 block keeps one inner face column, one face row and one corner.
self.assertEqual(len(closed.halo_dst), 4 * (3 + 4 + 1))
def test_pack_round_trip_and_exterior_stays_invalid(self):
for ny, nx, by, bx, h in CASES:
for periodic in PERIODIC:
layout = BlockLayout2D.build(ny, nx, by, bx, halo=h, periodic=periodic)
a = tags(ny, nx)
blocked = layout.to_blocked(a)
np.testing.assert_array_equal(layout.to_dense(blocked), a)
filled = np.isfinite(blocked[:, 0]).sum()
self.assertEqual(filled, ny * nx + len(layout.halo_dst))
flat = blocked.ravel()
for q in (0, 5):
np.testing.assert_array_equal(flat[layout.slot(layout.halo_dst, q).astype(np.intp)],
flat[layout.slot(layout.halo_src, q).astype(np.intp)])
def test_tagged_pull_matches_dense_pull(self):
for ny, nx, by, bx, h in CASES:
for periodic in PERIODIC:
with self.subTest(case=(ny, nx, by, bx, h), periodic=periodic):
layout = BlockLayout2D.build(ny, nx, by, bx, halo=h, periodic=periodic)
a = tags(ny, nx)
got = layout.to_dense(blocked_pull(layout, layout.to_blocked(a)))
np.testing.assert_array_equal(got, dense_pull(a, periodic))
def test_block_cell_resolves_periodic_halo_images(self):
layout = BlockLayout2D.build(6, 8, 3, 4)
ly, lx = layout.local_shape
# Block 0 sees x=7 (wrapped) in its west halo and y=5 in its south halo.
self.assertEqual(layout.block_cell(0, 0, 7), 1 * lx + 0)
self.assertEqual(layout.block_cell(0, 5, 0), 0 * lx + 1)
closed = BlockLayout2D.build(6, 8, 3, 4, periodic=(False, False))
with self.assertRaises(ValueError):
closed.block_cell(0, 0, 7)
with self.assertRaises(ValueError):
layout.block_cell(0, 4, 0) # two rows past the one-cell halo
def test_invalid_inputs_rejected(self):
for args, kw in (((6, 8, 4, 4), {}), ((6, 8, 3, 4), {"halo": 0}),
((6, 8, 3, 4), {"halo": 4}), ((6, 8, 3, 4), {"periodic": (1, 1)}),
((6, 8, 3, True), {}), ((6, 8.0, 3, 4), {})):
with self.assertRaises(ValueError):
BlockLayout2D.build(*args, **kw)
layout = BlockLayout2D.build(6, 8, 3, 4)
with self.assertRaises(ValueError):
layout.to_blocked(np.zeros((NQ, 6, 8), dtype=np.int64))
with self.assertRaises(ValueError):
layout.to_dense(np.zeros((4, NQ, 5, 5)))
def test_tables_are_readonly(self):
layout = BlockLayout2D.build(6, 8, 3, 4)
for array in (layout.origins, layout.owner, layout.halo_dst, layout.halo_src, layout.halo_kind):
self.assertFalse(array.flags.writeable)
if __name__ == "__main__":
unittest.main()