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test: add bounded N64 space-time GPU trajectory harness

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2026-10-18 09:32:21 -07:00
parent d61560d98a
commit 5dcd3e0dbe
3 changed files with 350 additions and 13 deletions
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tests/validation/multigrid/spacetime_gpu.py
+24 -13
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@@ -132,6 +132,7 @@ class SpaceTimeGPU:
self.ctx, self.mode, self.identity = context, mode, identity
self.allocations, self.modules, self.build_metadata = [], [], []
self.status, self.step_count, self.device_bytes = 'new', 0, 0
self.health_counts = np.zeros(6, np.uint64)
import pycuda.driver as cuda
from CelerisLab.cuda import compiler_v2 as compiler
root = Path(__file__).resolve().parents[3]
@@ -208,6 +209,7 @@ class SpaceTimeGPU:
self.status = 'failed'
raise
self.status, self.step_count = 'ready', 0
self.health_counts.fill(0)
def download(self):
if self.status != 'ready':
@@ -223,11 +225,12 @@ class SpaceTimeGPU:
a[:,~mask] = np.nan
return ref.cpu.State(*arrays, tick=2*self.step_count)
def step(self, *, mutation=0):
"""One audited interval; mutation 1/2/3 drops packets, 4 omits a ghost."""
if self.status != 'ready' or type(mutation) is not int or mutation not in range(5):
def step(self, *, mutation=0, audit=True):
"""One interval; audit=False skips only host ledger snapshots, never health checks."""
if (self.status != 'ready' or type(mutation) is not int or mutation not in range(5)
or type(audit) is not bool or (mutation and not audit)):
raise RuntimeError("ready owner and known test mutation required")
before = self.download()
before = self.download() if audit else None
n, nf, t = self.plan.n, self.plan.nf, self.device_tables
ng, nr = len(self.plan.groups), len(self.plan.receivers)
u32, null = np.uint32, np.uintp(0)
@@ -243,13 +246,16 @@ class SpaceTimeGPU:
self.launch(0, 'Collide', predicted,gp,null,omega[0],self.counts)
self.launch(0, 'Interpolate', g0,gp,t['samples'],t['origins'],t['sizes'],t['weights'],
self.pre,self.h,u32(ng),u32(self.mode=='frozen'),self.counts,count=ng)
coarse_g = self.read(g0,(9,n,n)); prediction = self.read(predicted,(9,n,n))
if audit:
coarse_g = self.read(g0,(9,n,n)); prediction = self.read(predicted,(9,n,n))
fine_phases = []
for m in (0,1):
f, out, g = self.fine
old_f = self.read(f,(9,nf,nf))
if audit:
old_f = self.read(f,(9,nf,nf))
self.launch(1, 'Collide', f,g,self.active,omega[1],self.counts)
fine_phases.append((old_f,self.read(g,(9,nf,nf))))
if audit:
fine_phases.append((old_f,self.read(g,(9,nf,nf))))
self.launch(0, 'Register', predicted,g,self.h,t['targets'],t['sources'],t['times'],
self.registers,u32(nr),np.int32(m),np.int32(mutation),count=nr)
rows = self.tables[f'incoming{m}']
@@ -258,14 +264,19 @@ class SpaceTimeGPU:
self.fine[0], self.fine[1] = out, f
self.launch(0, 'ApplyRegisters', predicted,self.registers,t['targets'],u32(nr),self.counts,count=nr)
counts = self.read(self.counts,(6,),np.uint32)
self.health_counts += counts.astype(np.uint64)
if counts.any():
raise AssertionError(f"boundary/leaf health failed: {counts.tolist()}")
coarse_after = self.read(predicted,(9,n,n))
coarse_after[:,~self.plan.maps.coarse_active] = np.nan
after = ref.cpu.State(coarse_after,self.read(self.fine[0],(9,nf,nf)),tick=2*(self.step_count+1))
ledger = rounding_ledger(self.plan,self.tables,before,after,coarse_g,prediction,fine_phases,
self.read(self.pre,(ng,4),np.float64),self.read(self.h,(ng,4)),
self.read(self.registers,(nr,),np.float64))
ledger = dict(boundary_budget_status='not_measured',unexplained=None)
if audit:
coarse_after = self.read(predicted,(9,n,n))
coarse_after[:,~self.plan.maps.coarse_active] = np.nan
after = ref.cpu.State(coarse_after,self.read(self.fine[0],(9,nf,nf)),tick=2*(self.step_count+1))
ledger = rounding_ledger(self.plan,self.tables,before,after,coarse_g,prediction,fine_phases,
self.read(self.pre,(ng,4),np.float64),self.read(self.h,(ng,4)),
self.read(self.registers,(nr,),np.float64))
ledger['boundary_budget_status'] = 'measured'
ledger['health_counts'] = counts.tolist()
self.coarse[0], self.coarse[2] = predicted, fc
self.step_count += 1
self.status = 'ready'