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fix ADM Constrant Violation Analysis

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This commit is contained in:
ianchb
2026-04-15 08:37:17 +08:00
parent 8fe60ea703
commit bb20c9a876
4 changed files with 63 additions and 6 deletions
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35
AMSS_NCKU_source/bssn_class.C
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@@ -89,6 +89,16 @@ bool bssn_cuda_use_resident_sync(int lev)
#endif
}
bool bssn_constraint_recompute_from_state(int lev, bool level0_cache_valid)
{
#if USE_CUDA_BSSN
return lev > 0 || !level0_cache_valid;
#else
(void)level0_cache_valid;
return lev > 0;
#endif
}
bool bssn_cuda_sync_subset(Block *cg,
int subset_count,
const int *state_indices,
@@ -361,6 +371,7 @@ bssn_class::bssn_class(double Couranti, double StartTimei, double TotalTimei,
int a_levi, int maxli, int decni, double maxrexi, double drexi)
: Courant(Couranti), StartTime(StartTimei), TotalTime(TotalTimei),
DumpTime(DumpTimei), d2DumpTime(d2DumpTimei), CheckTime(CheckTimei), AnasTime(AnasTimei),
cuda_level0_constraint_cache_valid(false),
Symmetry(Symmetryi), checkrun(checkruni), numepss(numepssi), numepsb(numepsbi), numepsh(numepshi),
#ifdef With_AHF
xc(0), yc(0), zc(0), xr(0), yr(0), zr(0), trigger(0), dTT(0), dumpid(0),
@@ -2448,6 +2459,8 @@ void bssn_class::Evolve(int Steps)
for (int ncount = 1; ncount < Steps + 1; ncount++)
{
cuda_level0_constraint_cache_valid = false;
// special for large mass ratio consideration
// if(fabs(Porg0[0][0]-Porg0[1][0])+fabs(Porg0[0][1]-Porg0[1][1])+fabs(Porg0[0][2]-Porg0[1][2])<1e-6)
// { GH->levels=GH->movls; }
@@ -3337,6 +3350,8 @@ void bssn_class::Step(int lev, int YN)
#else
const bool use_cuda_resident_sync = false;
#endif
const bool need_cuda_level0_constraint_cache =
(lev == 0) && (LastConsOut + dT * pow(0.5, Mymax(0, trfls)) >= AnasTime);
// new code 2013-2-15, zjcao
#if (MAPBH == 1)
@@ -3457,6 +3472,22 @@ void bssn_class::Step(int lev, int YN)
<< cg->bbox[2] << ":" << cg->bbox[5] << ")" << endl;
ERROR = 1;
}
if (need_cuda_level0_constraint_cache)
{
double *constraint_out[7] = {
cg->fgfs[Cons_Ham->sgfn], cg->fgfs[Cons_Px->sgfn], cg->fgfs[Cons_Py->sgfn], cg->fgfs[Cons_Pz->sgfn],
cg->fgfs[Cons_Gx->sgfn], cg->fgfs[Cons_Gy->sgfn], cg->fgfs[Cons_Gz->sgfn]};
if (bssn_cuda_download_constraint_outputs(cg->shape, constraint_out))
{
cout << "CUDA predictor constraint download failed in domain: ("
<< cg->bbox[0] << ":" << cg->bbox[3] << ","
<< cg->bbox[1] << ":" << cg->bbox[4] << ","
<< cg->bbox[2] << ":" << cg->bbox[5] << ")" << endl;
ERROR = 1;
}
else
cuda_level0_constraint_cache_valid = true;
}
used_gpu_substep = true;
used_gpu_resident_state = (keep_resident_state != 0);
}
@@ -7734,7 +7765,7 @@ void bssn_class::Constraint_Out()
for (int lev = 0; lev < GH->levels; lev++)
{
// make sure the data consistent for higher levels
if (lev > 0) // if the constrait quantities can be reused from the step rhs calculation
if (bssn_constraint_recompute_from_state(lev, cuda_level0_constraint_cache_valid))
{
double TRK4 = PhysTime;
double ndeps = numepsb;
@@ -8237,7 +8268,7 @@ void bssn_class::Interp_Constraint(bool infg)
for (int lev = 0; lev < GH->levels; lev++)
{
// make sure the data consistent for higher levels
if (lev > 0) // if the constrait quantities can be reused from the step rhs calculation
if (bssn_constraint_recompute_from_state(lev, cuda_level0_constraint_cache_valid))
{
double TRK4 = PhysTime;
double ndeps = numepsb;