Merge claude/block-gpu-periodic for bounded integration validation
This commit is contained in:
Frank14f
@@ -0,0 +1,201 @@
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# CelerisLab/lbm/block_stepper.py
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"""Opt-in body-free periodic backend for one BlockLayout2D level.
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D2Q9/SRT/FP32 unforced double buffers. Each step refreshes every halo from
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its owner core, then pulls/collides core cells into the spare buffer, then
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swaps. Only halo pair tables are uploaded; dense ownership stays on the host.
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The caller owns the CudaContext and must close this backend before it.
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No bodies, walls, refinement, checkpoint or runtime parameter mutation;
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wall/slot/inlet fields in cfg are ignored (fully periodic level).
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"""
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from dataclasses import replace
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from numbers import Integral
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import struct
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from threading import RLock
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import numpy as np
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import pycuda.driver as cuda
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from ..cuda import compiler_v2 as compiler
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from .blocks import NQ, BlockLayout2D
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MAX_GRID_DIM = 65535 # CUDA gridDim.y/z limit (rows, blocks)
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class PeriodicBlockStepper:
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"""G->G stepping of Q-major (9, ny, nx) postcollision populations.
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On a device/launch failure the instance becomes unusable: close and
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recreate it rather than assuming a partially advanced buffer rolled back.
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"""
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def __init__(self, cfg, layout, *, context):
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if not isinstance(layout, BlockLayout2D) or layout.periodic != (True, True):
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raise ValueError("PeriodicBlockStepper requires a doubly periodic BlockLayout2D")
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checked = replace(cfg)
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checked.validate()
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if (not checked.is_d2q9 or checked.collision != "SRT"
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or checked.streaming != "double_buffer" or checked.store_precision != "FP32"
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or checked.ddf_shifting or checked.les_enabled
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or (checked.ny, checked.nx) != layout.shape):
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raise ValueError("PeriodicBlockStepper requires matching D2Q9/SRT/FP32/"
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"unshifted/double_buffer config without LES")
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ly, lx = layout.local_shape
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pairs = len(layout.halo_dst)
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tpb = checked.threads_per_block
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if layout.nblocks > MAX_GRID_DIM or ly > MAX_GRID_DIM or not 0 < pairs < 2**31:
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raise ValueError("block count, block rows or halo pairs exceed launch limits")
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self.layout = layout
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self.ctx = context
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# Wall/slot fields are not applied; neutralize them like the fine patch level.
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self._local_cfg = replace(checked, nx=lx, ny=ly, y_wall_bc="bounce_back", top_wall_bc="velocity",
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wall_slot_width=0, wall_normal_velocity=0.0, velocity=0.0)
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self._block = (tpb, 1, 1)
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self._grid = ((lx + tpb - 1) // tpb, ly, layout.nblocks)
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self._copy_grid = ((pairs + tpb - 1) // tpb, 1)
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self._bytes = int(np.prod(layout.blocked_shape)) * 4
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self._lock = RLock()
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self._status = "new"
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self._step_count = 0
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self._allocations = []
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self._stream = self._module = self._copy = self._step = None
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with self.ctx.activate():
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try:
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free, _ = cuda.mem_get_info()
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if 2 * self._bytes + layout.halo_dst.nbytes + layout.halo_src.nbytes > free:
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raise MemoryError("blocked buffers exceed free device memory")
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self._stream = cuda.Stream()
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config = self._local_cfg
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config.validate()
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if not np.isclose(config.omega, 1 / (3 * checked.viscosity + .5), rtol=1e-14, atol=0):
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raise RuntimeError("block omega/tau mismatch")
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build = compiler.generate_config(config)
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try:
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ptx = compiler.compile_kernel(self.ctx.sm_arch, source="blocks.cu", build_dir=build)
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module = compiler.load_module(ptx)
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finally:
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compiler.cleanup_build_dir(build)
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ptr, size = module.get_global("d_params")
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if size != struct.calcsize("=ffffI"):
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raise RuntimeError("LBMParams host/device layout mismatch")
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cuda.memcpy_htod(ptr, struct.pack("=ffffI", config.omega, 0, 0, 0, 0))
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self._module = module
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self._current = self._allocate(self._bytes)
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self._spare = self._allocate(self._bytes)
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self._dst = self._upload(layout.halo_dst)
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self._src = self._upload(layout.halo_src)
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self._copy = module.get_function("BlockHaloCopy")
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self._step = module.get_function("BlockStep")
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except BaseException:
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try:
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self.close()
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except Exception:
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pass # Preserve the original construction failure.
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raise
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def _allocate(self, size):
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pointer = cuda.mem_alloc(size)
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self._allocations.append(pointer)
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return pointer
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def _upload(self, array):
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array = np.ascontiguousarray(array)
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pointer = self._allocate(array.nbytes)
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cuda.memcpy_htod(pointer, array)
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return pointer
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def _require(self, *states):
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if self._status not in states:
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raise RuntimeError(f"Block stepper is {self._status}; expected {' or '.join(states)}")
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@property
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def step_count(self):
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return self._step_count
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def initialize(self, g):
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"""Upload dense G_0; the spare buffer starts NaN so stale halos cannot hide."""
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with self._lock, self.ctx.activate():
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self._require("new", "ready")
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dense = np.array(g, dtype=np.float32, order="C", copy=True)
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if dense.shape != (NQ, *self.layout.shape):
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raise ValueError("Expected a Q-major (9, ny, nx) array")
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if not np.isfinite(dense).all() or (dense.sum(axis=0) <= 0).any():
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raise ValueError("Populations must be finite with positive density")
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blocked = self.layout.to_blocked(dense)
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spare = np.full_like(blocked, np.nan)
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try:
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cuda.memcpy_htod(self._current, blocked)
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cuda.memcpy_htod(self._spare, spare)
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self._step_count = 0
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self._status = "ready"
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except BaseException:
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self._status = "failed"
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raise
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def step(self, n=1):
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"""Advance n steps: halo refresh, then core pull/collide, per step."""
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if isinstance(n, bool) or not isinstance(n, Integral) or n < 0:
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raise ValueError("n must be a nonnegative integer")
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with self._lock, self.ctx.activate():
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self._require("ready")
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kw = dict(block=self._block, stream=self._stream)
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try:
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self._status = "advancing"
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for _ in range(n):
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self._copy(self._current, self._dst, self._src,
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np.uint32(len(self.layout.halo_dst)), grid=self._copy_grid, **kw)
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self._step(self._current, self._spare, np.uint32(self.layout.halo),
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grid=self._grid, **kw)
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self._stream.synchronize()
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self._current, self._spare = self._spare, self._current
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self._step_count += 1
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self._status = "ready"
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except BaseException:
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self._status = "failed"
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raise
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def download(self):
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"""Return dense (9, ny, nx) FP32 core populations; no host cache."""
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with self._lock, self.ctx.activate():
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self._require("ready")
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blocked = np.empty(self.layout.blocked_shape, np.float32)
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try:
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cuda.memcpy_dtoh(blocked, self._current)
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except BaseException:
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self._status = "failed"
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raise
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return self.layout.to_dense(blocked)
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def close(self):
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"""Release owned resources; retain them for retry if context activation fails."""
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with self._lock:
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if self._status == "closed":
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return
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self._status = "failed"
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with self.ctx.activate():
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self._status = "closed"
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error = None
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try:
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if self._stream is not None:
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self._stream.synchronize()
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except Exception as exc:
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error = exc
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self._copy = self._step = self._module = None
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for pointer in self._allocations:
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try:
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pointer.free()
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except Exception as exc:
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error = error or exc
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self._allocations.clear()
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self._stream = None
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if error is not None:
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raise error
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def __enter__(self):
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return self
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def __exit__(self, *exc):
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try:
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self.close()
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except Exception:
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if exc[0] is None:
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raise
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@@ -0,0 +1,49 @@
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// CelerisLab/lbm/kernels/blocks.cu
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// One periodic level of fixed-size blocks (lbm/blocks.py layout). Separate
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// compilation entry: NX, NY are the block window including halo, so index_f
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// and linear_index address one block; blockIdx.z selects the block, whose
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// populations start at b*NQ*TOTAL_CELLS (block-contiguous, Q-major inside).
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#include <stdint.h>
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#include "config.h"
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#include "core/precision.cuh"
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#include "core/descriptors.cuh"
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#include "core/layout.cuh"
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#include "core/params.cuh"
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#include "operators/macro.cuh"
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#include "operators/collision_srt.cuh"
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#include "streaming/pull_double_buffer.cuh"
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#if DIM != 2 || NQ != 9 || COLLISION_MODEL != 0 || STORE_PRECISION != 0 || USE_DDF_SHIFTING || USE_LES || STREAMING_MODEL != 0
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#error "Blocks require unshifted FP32 D2Q9 SRT double buffers without LES"
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#endif
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// Halo refresh: block cell ids b*TOTAL_CELLS+c, sources are always core cells.
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extern "C" __global__ void BlockHaloCopy(
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fpxx* f, const uint64_t* dst, const uint64_t* src, unsigned int count)
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{
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unsigned int row = blockIdx.x * blockDim.x + threadIdx.x;
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if (row >= count) return;
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const uint64_t d = dst[row], s = src[row];
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fpxx* to = f + (d / TOTAL_CELLS) * NQ * TOTAL_CELLS;
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const fpxx* from = f + (s / TOTAL_CELLS) * NQ * TOTAL_CELLS;
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for (unsigned int q = 0; q < NQ; ++q)
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to[index_f(d % TOTAL_CELLS, q)] = from[index_f(s % TOTAL_CELLS, q)];
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}
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// Pull/collide/store core cells only; halo cells of out are left untouched.
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extern "C" __global__ void BlockStep(const fpxx* in, fpxx* out, unsigned int halo) {
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unsigned int x, y; unsigned long k;
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index_from_thread(x, y, k);
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if (x < halo || y < halo || x >= NX - halo || y >= NY - halo) return;
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const unsigned long base = (unsigned long)blockIdx.z * NQ * TOTAL_CELLS;
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in += base;
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out += base;
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unsigned long j[NQ];
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compute_neighbors(x, y, j); // Core neighbors stay inside the window: no wrap.
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float f[NQ], rho, ux, uy, feq[NQ];
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stream_pull_load(k, f, in, j);
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compute_rho_u(f, rho, ux, uy);
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compute_feq(rho, ux, uy, feq);
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collide_srt_no_force(f, feq, d_params.omega);
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stream_pull_store(k, f, out);
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}
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@@ -0,0 +1,216 @@
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"""Periodic body-free block backend: CPU contract doubles plus one short GPU case.
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Frozen GPU gates (32x24, 8 steps, positive low-Mach non-equilibrium state):
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finite cores; bit-identical 1x1, 2x2 and 4x2 splits; max |G - FP64 oracle|
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<= 3e-6. Mass/momentum drift is reported, not gated.
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"""
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from contextlib import nullcontext
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from pathlib import Path
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import resource
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from threading import RLock
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import unittest
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from unittest.mock import MagicMock, Mock, patch
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import numpy as np
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import pycuda.driver as cuda
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from CelerisLab.config import LBMConfig
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from CelerisLab.cuda import compiler_v2 as compiler
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from CelerisLab.lbm import block_stepper as implementation
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from CelerisLab.lbm.blocks import BlockLayout2D
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from CelerisLab.lbm.block_stepper import PeriodicBlockStepper
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from CelerisLab.lbm.descriptors import D2Q9_EX, D2Q9_EY
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ROOT = Path(__file__).resolve().parents[3]
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NX, NY, NU, STEPS, ORACLE_ATOL = 32, 24, .1, 8, 3e-6
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SPLITS = ((24, 32), (12, 16), (12, 8)) # 1x1, 2x2, 4x2 blocks (by, bx)
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W = np.array([4 / 9] + [1 / 9] * 4 + [1 / 36] * 4)
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CX, CY = np.array(D2Q9_EX, float), np.array(D2Q9_EY, float)
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def config(**kwargs):
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return LBMConfig(**dict(nx=NX, ny=NY, viscosity=NU, **kwargs))
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def feq(rho, ux, uy):
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cu = CX[:, None, None] * ux + CY[:, None, None] * uy
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return W[:, None, None] * rho * (1 + 3 * cu + 4.5 * cu * cu - 1.5 * (ux * ux + uy * uy))
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def initial_state():
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"""Positive low-Mach equilibrium plus a seeded non-equilibrium part."""
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y, x = np.mgrid[0:NY, 0:NX]
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rho = 1 + 1e-3 * np.cos(2 * np.pi * x / NX)
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ux = .02 * np.sin(2 * np.pi * y / NY)
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uy = .01 * np.cos(2 * np.pi * x / NX)
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noise = np.random.default_rng(2026).uniform(-1, 1, (9, NY, NX)) * 1e-3 * W[:, None, None]
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return (feq(rho, ux, uy) + noise).astype(np.float32)
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def oracle(g, steps):
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"""FP64 periodic pull + SRT, from the same FP32-rounded G_0."""
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g = g.astype(np.float64)
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omega = 1 / (3 * NU + .5)
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for _ in range(steps):
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f = np.stack([np.roll(g[q], (D2Q9_EY[q], D2Q9_EX[q]), axis=(0, 1)) for q in range(9)])
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rho = f.sum(axis=0)
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ux, uy = (CX[:, None, None] * f).sum(axis=0) / rho, (CY[:, None, None] * f).sum(axis=0) / rho
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g = f + omega * (feq(rho, ux, uy) - f)
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return g
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def totals(g):
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g = g.astype(np.float64)
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return g.sum(), (CX[:, None, None] * g).sum(), (CY[:, None, None] * g).sum()
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class CpuContracts(unittest.TestCase):
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"""No device: driver doubles prove rejection before allocation and lifecycle."""
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def forbidden_context(self):
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return Mock(activate=Mock(side_effect=AssertionError("CUDA reached")), sm_arch="sm_70")
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def test_unsupported_inputs_rejected_before_cuda(self):
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layout = BlockLayout2D.build(NY, NX, 12, 16)
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cases = ((config(), BlockLayout2D.build(NY, NX, 12, 16, periodic=(True, False))),
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(config(), BlockLayout2D.build(NY, NX * 2, 12, 16)),
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(config(collision="MRT"), layout),
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(config(), "layout"))
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for cfg, lay in cases:
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with self.subTest(cfg=cfg.collision, layout=getattr(lay, "periodic", lay)):
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with self.assertRaises(ValueError):
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PeriodicBlockStepper(cfg, lay, context=self.forbidden_context())
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with patch.object(implementation, "MAX_GRID_DIM", 3):
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with self.assertRaisesRegex(ValueError, "launch limits"):
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PeriodicBlockStepper(config(), layout, context=self.forbidden_context())
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def test_memory_and_param_layout_rejected_before_allocation(self):
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layout = BlockLayout2D.build(NY, NX, 12, 16)
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context = Mock(activate=nullcontext, sm_arch="sm_70")
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with patch.object(cuda, "mem_get_info", return_value=(1024, 1 << 30)), \
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patch.object(cuda, "Stream") as stream, patch.object(cuda, "mem_alloc") as alloc:
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with self.assertRaises(MemoryError):
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PeriodicBlockStepper(config(), layout, context=context)
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stream.assert_not_called()
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alloc.assert_not_called()
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module = Mock()
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module.get_global.return_value = (Mock(), 16)
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with patch.object(cuda, "mem_get_info", return_value=(1 << 30, 1 << 30)), \
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patch.object(cuda, "Stream"), patch.object(compiler, "generate_config"), \
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patch.object(compiler, "compile_kernel") as compile_kernel, \
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patch.object(compiler, "cleanup_build_dir"), \
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patch.object(compiler, "load_module", return_value=module), \
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patch.object(cuda, "mem_alloc") as alloc, patch.object(cuda, "memcpy_htod") as upload:
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with self.assertRaisesRegex(RuntimeError, "layout mismatch"):
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PeriodicBlockStepper(config(), layout, context=context)
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self.assertEqual(compile_kernel.call_args.kwargs["source"], "blocks.cu")
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alloc.assert_not_called()
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upload.assert_not_called()
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def fake_backend(self):
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backend = PeriodicBlockStepper.__new__(PeriodicBlockStepper)
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backend.layout = BlockLayout2D.build(NY, NX, 12, 16)
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backend.ctx = Mock(activate=nullcontext)
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backend._lock = RLock()
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backend._status = "ready"
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backend._step_count = 0
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backend._stream = Mock()
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backend._module = Mock()
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backend._copy = backend._step = Mock()
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backend._dst, backend._src = Mock(), Mock()
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backend._block, backend._grid, backend._copy_grid = (32, 1, 1), (1, 1, 1), (1, 1)
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backend._allocations = [Mock(), Mock()]
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backend._current, backend._spare = backend._allocations
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return backend
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def test_initialize_rejects_bad_state_before_upload(self):
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backend = self.fake_backend()
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good = initial_state()
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bad = (good[:, :-1], np.where(np.arange(NX) == 3, np.nan, good), -good)
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with patch.object(cuda, "memcpy_htod") as upload:
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for g in bad:
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with self.assertRaises(ValueError):
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backend.initialize(g)
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upload.assert_not_called()
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backend.initialize(good)
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self.assertEqual(upload.call_count, 2)
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self.assertTrue(np.isnan(upload.call_args_list[1].args[1]).all())
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backend.close()
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def test_failed_launch_and_download_make_backend_unusable(self):
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for failure in ("step", "download"):
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backend = self.fake_backend()
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if failure == "step":
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||||
backend._step = Mock(side_effect=RuntimeError("launch failed"))
|
||||
with self.assertRaisesRegex(RuntimeError, "launch failed"):
|
||||
backend.step()
|
||||
else:
|
||||
with patch.object(cuda, "memcpy_dtoh", side_effect=RuntimeError("read failed")):
|
||||
with self.assertRaisesRegex(RuntimeError, "read failed"):
|
||||
backend.download()
|
||||
for operation in (backend.download, backend.step):
|
||||
with self.assertRaisesRegex(RuntimeError, "failed"):
|
||||
operation()
|
||||
backend.close()
|
||||
for allocation in backend_allocations(backend):
|
||||
allocation.free.assert_called_once()
|
||||
|
||||
def test_activation_failure_retains_resources_for_retry(self):
|
||||
backend = self.fake_backend()
|
||||
allocations, stream, module = backend._allocations[:], backend._stream, backend._module
|
||||
unavailable = MagicMock()
|
||||
unavailable.__enter__.side_effect = RuntimeError("activation failed")
|
||||
backend.ctx.activate = Mock(side_effect=[unavailable, nullcontext()])
|
||||
with self.assertRaisesRegex(RuntimeError, "activation failed"):
|
||||
backend.close()
|
||||
self.assertEqual(backend._status, "failed")
|
||||
self.assertEqual(backend._allocations, allocations)
|
||||
self.assertIs(backend._stream, stream)
|
||||
self.assertIs(backend._module, module)
|
||||
backend.close()
|
||||
self.assertEqual(backend._status, "closed")
|
||||
self.assertIsNone(backend._module)
|
||||
self.assertIsNone(backend._copy)
|
||||
self.assertIsNone(backend._step)
|
||||
for allocation in allocations:
|
||||
allocation.free.assert_called_once()
|
||||
|
||||
|
||||
def backend_allocations(backend):
|
||||
return (backend._current, backend._spare)
|
||||
|
||||
|
||||
class PeriodicBlockGPU(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.assertEqual(Path(implementation.__file__).resolve(),
|
||||
ROOT / "src/CelerisLab/lbm/block_stepper.py")
|
||||
|
||||
def tearDown(self):
|
||||
rss = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1024
|
||||
print(f"host_peak_rss={rss:.3f} MiB", flush=True)
|
||||
|
||||
def test_splits_bit_identical_and_fp64_oracle(self):
|
||||
from CelerisLab.cuda.context import CudaContext
|
||||
g0 = initial_state()
|
||||
results = []
|
||||
with CudaContext(0) as context:
|
||||
for by, bx in SPLITS:
|
||||
layout = BlockLayout2D.build(NY, NX, by, bx)
|
||||
with PeriodicBlockStepper(config(), layout, context=context) as backend:
|
||||
backend.initialize(g0)
|
||||
backend.step(STEPS)
|
||||
self.assertEqual(backend.step_count, STEPS)
|
||||
results.append(backend.download())
|
||||
for (by, bx), g in zip(SPLITS, results):
|
||||
self.assertTrue(np.isfinite(g).all(), (by, bx))
|
||||
np.testing.assert_array_equal(g, results[0], err_msg=f"split {(by, bx)}")
|
||||
error = np.abs(results[0].astype(np.float64) - oracle(g0, STEPS)).max()
|
||||
before, after = totals(g0), totals(results[0])
|
||||
print(f"max_abs_oracle_error={error:.3e} gate={ORACLE_ATOL:.0e}", flush=True)
|
||||
print("drift mass={:.3e} jx={:.3e} jy={:.3e}".format(
|
||||
*(a - b for a, b in zip(after, before))), flush=True)
|
||||
self.assertLessEqual(error, ORACLE_ATOL)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
Reference in New Issue
Block a user