def ParMultComplex(A, B):
'''
compute complex mult of hypre real matrices
A = (R_A, I_A)
B = (R_B, I_B)
(R_A*R_B - I_A*I_B, R_A*I_B + I_A*R_B)
'''
from mpi4py import MPI
import mfem.par as mfem
comm = MPI.COMM_WORLD
num_proc = MPI.COMM_WORLD.size
myid = MPI.COMM_WORLD.rank
R_A, I_A = A
R_B, I_B = B
if I_A is None and I_B is None:
r = mfem.ParMult(R_A, R_B)
r.CopyRowStarts()
r.CopyColStarts()
return (r, None)
elif I_A is None:
r = mfem.ParMult(R_A, R_B)
i = mfem.ParMult(R_A, I_B)
r.CopyRowStarts()
r.CopyColStarts()
i.CopyRowStarts()
i.CopyColStarts()
return (r, i)
elif I_B is None:
r = mfem.ParMult(R_A, R_B)
i = mfem.ParMult(I_A, R_B)
r.CopyRowStarts()
r.CopyColStarts()
i.CopyRowStarts()
i.CopyColStarts()
return (r, i)
else:
A = mfem.ParMult(R_A, R_B)
B = mfem.ParMult(I_A, I_B)
C = mfem.ParMult(R_A, I_B)
D = mfem.ParMult(I_A, R_B)
col_starts = A.GetColPartArray()
col_starts[2] = A.N()
r = ToHypreParCSR((ToScipyCoo(A) - ToScipyCoo(B)).tocsr(),
col_starts=col_starts)
i = ToHypreParCSR((ToScipyCoo(C) + ToScipyCoo(D)).tocsr(),
col_starts=col_starts)
return (r, i)
def schur(*names, **kwargs):
# shucr("A1", "B1", scale=(1.0, 1e3))
prc = kwargs.pop('prc')
blockname = kwargs.pop('blockname')
r0 = prc.get_row_by_name(blockname)
c0 = prc.get_col_by_name(blockname)
A0 = prc.get_operator_block(r0, c0)
scales = kwargs.pop('scale', [1] * len(names))
print_level = kwargs.pop('print_level', -1)
for name, scale in zip(names, scales):
r1 = prc.get_row_by_name(name)
c1 = prc.get_col_by_name(name)
B = prc.get_operator_block(r0, c1)
Bt = prc.get_operator_block(r1, c0)
Bt = Bt.Copy()
B0 = get_block(A, r1, c1)
if use_parallel:
Md = mfem.HyprePaarVector(MPI.COMM_WORLD, B0.GetGlobalNumRows(),
B0.GetColStarts())
else:
Md = mfem.Vector()
A0.GetDiag(Md)
Md *= scale
if use_parallel:
Bt.InvScaleRows(Md)
S = mfem.ParMult(B, Bt)
invA0 = mfem.HypreBoomerAMG(S)
else:
S = mfem.Mult(B, Bt)
invA0 = mfem.DSmoother(S)
invA0.iterative_mode = False
invA0.SetPrintLevel(print_level)
return invA0
def schur(*names, **kwargs):
# schur("A1", "B1", scale=(1.0, 1e3))
prc = kwargs.pop('prc')
blockname = kwargs.pop('blockname')
r0 = prc.get_row_by_name(blockname)
c0 = prc.get_col_by_name(blockname)
scales = kwargs.pop('scale', [1] * len(names))
print_level = kwargs.pop('print_level', -1)
S = []
for name, scale in zip(names, scales):
r1 = prc.get_row_by_name(name)
c1 = prc.get_col_by_name(name)
B = prc.get_operator_block(r0, c1)
Bt = prc.get_operator_block(r1, c0)
B0 = prc.get_operator_block(r1, c1)
if use_parallel:
Bt = Bt.Transpose()
Bt = Bt.Transpose()
Md = mfem.HypreParVector(MPI.COMM_WORLD, B0.GetGlobalNumRows(),
B0.GetColStarts())
else:
Bt = Bt.Copy()
Md = mfem.Vector()
B0.GetDiag(Md)
Md *= scale
if use_parallel:
Bt.InvScaleRows(Md)
S.append(mfem.ParMult(B, Bt))
else:
S.append(mfem.Mult(B, Bt))
if use_parallel:
from mfem.common.parcsr_extra import ToHypreParCSR, ToScipyCoo
S2 = [ToScipyCoo(s) for s in S]
for s in S2[1:]:
S2[0] = S2[0] + s
S = ToHypreParCSR(S2[0].tocsr())
invA0 = mfem.HypreBoomerAMG(S)
else:
from mfem.common.sparse_utils import sparsemat_to_scipycsr
S2 = [sparsemat_to_scipycsr(s).tocoo() for s in S]
for s in S2[1:]:
S2[0] = S2[0] + s
S = mfem.SparseMatrix(S2.tocsr())
invA0 = mfem.DSmoother(S)
invA0.iterative_mode = False
invA0.SetPrintLevel(print_level)
invA0._S = S
return invA0
def solve_parallel(self, A, b, x=None):
from mpi4py import MPI
myid = MPI.COMM_WORLD.rank
nproc = MPI.COMM_WORLD.size
from petram.helper.mpi_recipes import gather_vector
def get_block(Op, i, j):
try:
return Op._linked_op[(i, j)]
except KeyError:
return None
offset = A.RowOffsets()
rows = A.NumRowBlocks()
cols = A.NumColBlocks()
if self.gui.write_mat:
for i in range(cols):
for j in range(rows):
m = get_block(A, i, j)
if m is None: continue
m.Print('matrix_' + str(i) + '_' + str(j))
for i, bb in enumerate(b):
for j in range(rows):
v = bb.GetBlock(j)
v.Print('rhs_' + str(i) + '_' + str(j) + '.' + smyid)
if x is not None:
for j in range(rows):
xx = x.GetBlock(j)
xx.Print('x_' + str(i) + '_' + str(j) + '.' + smyid)
M = mfem.BlockDiagonalPreconditioner(offset)
prcs = dict(self.gui.preconditioners)
name = self.Aname
assert not self.gui.parent.is_complex(), "can not solve complex"
if self.gui.parent.is_converted_from_complex():
name = sum([[n, n] for n in name], [])
for k, n in enumerate(name):
prc = prcs[n][1]
if prc == "None": continue
name = "".join([tmp for tmp in prc if not tmp.isdigit()])
A0 = get_block(A, k, k)
if A0 is None and not name.startswith('schur'): continue
if hasattr(mfem.HypreSmoother, prc):
invA0 = mfem.HypreSmoother(A0)
invA0.SetType(getattr(mfem.HypreSmoother, prc))
elif prc == 'ams':
depvar = self.engine.r_dep_vars[k]
dprint1("setting up AMS for ", depvar)
prec_fespace = self.engine.fespaces[depvar]
invA0 = mfem.HypreAMS(A0, prec_fespace)
invA0.SetSingularProblem()
elif name == 'MUMPS':
cls = SparseSmootherCls[name][0]
invA0 = cls(A0, gui=self.gui[prc], engine=self.engine)
elif name.startswith('schur'):
args = name.split("(")[-1].split(")")[0].split(",")
dprint1("setting up schur for ", args)
if len(args) > 1:
assert False, "not yet supported"
for arg in args:
r1 = self.engine.dep_var_offset(arg.strip())
c1 = self.engine.r_dep_var_offset(arg.strip())
B = get_block(A, k, c1)
Bt = get_block(A, r1, k).Transpose()
Bt = Bt.Transpose()
B0 = get_block(A, r1, c1)
Md = mfem.HypreParVector(MPI.COMM_WORLD,
B0.GetGlobalNumRows(),
B0.GetColStarts())
B0.GetDiag(Md)
Bt.InvScaleRows(Md)
S = mfem.ParMult(B, Bt)
invA0 = mfem.HypreBoomerAMG(S)
invA0.iterative_mode = False
else:
cls = SparseSmootherCls[name][0]
invA0 = cls(A0, gui=self.gui[prc])
invA0.iterative_mode = False
M.SetDiagonalBlock(k, invA0)
'''
We should support Shur complement type preconditioner
if offset.Size() > 2:
B = get_block(A, 1, 0)
MinvBt = get_block(A, 0, 1)
#Md = mfem.HypreParVector(MPI.COMM_WORLD,
# A0.GetGlobalNumRows(),
# A0.GetRowStarts())
Md = mfem.Vector()
A0.GetDiag(Md)
MinvBt.InvScaleRows(Md)
S = mfem.ParMult(B, MinvBt)
invS = mfem.HypreBoomerAMG(S)
invS.iterative_mode = False
M.SetDiagonalBlock(1, invS)
'''
maxiter = int(self.maxiter)
atol = self.abstol
rtol = self.reltol
kdim = int(self.kdim)
printit = 1
sol = []
solver = mfem.GMRESSolver(MPI.COMM_WORLD)
solver.SetKDim(kdim)
#solver = mfem.MINRESSolver(MPI.COMM_WORLD)
#solver.SetOperator(A)
#solver = mfem.CGSolver(MPI.COMM_WORLD)
solver.SetOperator(A)
solver.SetAbsTol(atol)
solver.SetRelTol(rtol)
solver.SetMaxIter(maxiter)
solver.SetPreconditioner(M)
solver.SetPrintLevel(1)
# solve the problem and gather solution to head node...
# may not be the best approach
for bb in b:
rows = MPI.COMM_WORLD.allgather(np.int32(bb.Size()))
rowstarts = np.hstack((0, np.cumsum(rows)))
dprint1("rowstarts/offser", rowstarts, offset.ToList())
if x is None:
xx = mfem.BlockVector(offset)
xx.Assign(0.0)
else:
xx = x
#for j in range(cols):
# dprint1(x.GetBlock(j).Size())
# dprint1(x.GetBlock(j).GetDataArray())
#assert False, "must implement this"
solver.Mult(bb, xx)
s = []
for i in range(offset.Size() - 1):
v = xx.GetBlock(i).GetDataArray()
vv = gather_vector(v)
if myid == 0:
s.append(vv)
else:
pass
if myid == 0:
sol.append(np.hstack(s))
if myid == 0:
sol = np.transpose(np.vstack(sol))
return sol
else:
return None