def SetOperator(self, A, dist, name=None):
try:
from mpi4py import MPI
except:
from petram.helper.dummy_mpi import MPI
myid = MPI.COMM_WORLD.rank
nproc = MPI.COMM_WORLD.size
self.row_offsets = A.RowOffsets()
AA = build_csr_local(A, self.dtype, self.is_complex)
if self.gui.write_mat:
write_coo_matrix('matrix', AA.tocoo())
if dist:
self.spss.set_distributed_csr_matrix(AA)
else:
self.spss.set_csr_matrix(AA)
self._matrix = AA
def save_to_file(self, file):
for i in range(self.shape[0]):
for j in range(self.shape[1]):
name = file + '_' + str(i) + '_' + str(j)
v = self[i, j]
if isinstance(v, chypre.CHypreMat):
m = v.get_local_coo()
write_coo_matrix(name, m)
elif isinstance(v, chypre.CHypreVec):
m = coo_matrix(v.toarray()).transpose()
write_coo_matrix(name, m)
elif isinstance(v, ScipyCoo):
write_coo_matrix(name, v)
elif v is None:
continue
else:
assert False, "Don't know how to write file for " + \
str(type(v))
def SetOperator(self, A, dist, name=None, ifactor=0):
try:
from mpi4py import MPI
except BaseException:
from petram.helper.dummy_mpi import MPI
myid = MPI.COMM_WORLD.rank
nproc = MPI.COMM_WORLD.size
from petram.ext.mumps.mumps_solve import i_array
gui = self.gui
s = self.s
if dist:
dprint1("SetOperator distributed matrix")
A.eliminate_zeros()
if gui.write_mat:
write_coo_matrix('matrix', A)
if gui.write_inv:
smyid = '{:0>6d}'.format(myid)
np.savez("matrix." + smyid, A=A)
self._merge_coo_matrix(myid, nproc)
import petram.ext.mumps.mumps_solve as mumps_solve
dprint1('!!!these two must be consistent')
dprint1('sizeof(MUMPS_INT) ', mumps_solve.SIZEOF_MUMPS_INT())
# set matrix format
s.set_icntl(5, 0)
s.set_icntl(18, 3)
dprint1("NNZ local: ", A.nnz)
nnz_array = np.array(MPI.COMM_WORLD.allgather(A.nnz))
if myid == 0:
dprint1("NNZ all: ", nnz_array, np.sum(nnz_array))
s.set_n(A.shape[1])
dtype_int = 'int' + str(mumps_solve.SIZEOF_MUMPS_INT() * 8)
row = A.row
col = A.col
row = row.astype(dtype_int) + 1
col = col.astype(dtype_int) + 1
AA = self.make_matrix_entries(A)
if len(col) > 0:
dprint1('index data size ', type(col[0]))
dprint1('matrix data type ', type(AA[0]))
s.set_nz_loc(len(A.data))
s.set_irn_loc(i_array(row))
s.set_jcn_loc(i_array(col))
s.set_a_loc(self.data_array(AA))
self.dataset = (A.data, row, col)
self.irhs_loc = np.unique(row)
self.N_global = np.sum(MPI.COMM_WORLD.allgather(len(
self.irhs_loc)))
else:
A = A.tocoo(False) # .astype('complex')
import petram.ext.mumps.mumps_solve as mumps_solve
dprint1('!!!these two must be consistent')
dprint1('sizeof(MUMPS_INT) ', mumps_solve.SIZEOF_MUMPS_INT())
dtype_int = 'int' + str(mumps_solve.SIZEOF_MUMPS_INT() * 8)
if gui.write_mat:
# tocsr().tocoo() forces the output is row sorted.
write_coo_matrix('matrix', A.tocsr().tocoo())
# No outputs
if myid == 0:
row = A.row
col = A.col
row = row.astype(dtype_int) + 1
col = col.astype(dtype_int) + 1
AA = self.make_matrix_entries(A)
if len(col) > 0:
dprint1('index data size ', type(col[0]))
dprint1('matrix data type ', type(AA[0]))
s.set_n(A.shape[0])
s.set_nz(len(A.data))
s.set_irn(i_array(row))
s.set_jcn(i_array(col))
s.set_a(self.data_array(AA))
self.dataset = (A.data, row, col)
self.irhs_loc = np.unique(row)
self.N_global = len(self.irhs_loc)
else:
self.irhs_loc = None
self.N_global = None
if self.skip_solve:
print("skip solve is on.... returning")
return
# blr
if gui.use_blr:
s.set_icntl(35, 1)
s.set_cntl(7, float(gui.blr_drop))
# out-of-core
if gui.out_of_core:
s.set_icntl(22, 1)
if gui.icntl14.lower() != 'default':
# percentage increase in the estimated workingspace
s.set_icntl(14, convert2int(gui.icntl14))
if gui.icntl23.lower() != 'default':
# maximum size of the working memory
s.set_icntl(23, convert2int(gui.icntl23))
if gui.icntl8.lower() != 'default':
# the scaling strategy
s.set_icntl(8, convert2int(gui.icntl8))
if gui.icntl6.lower() != 'default':
# permutes the matrix to azero-freediagonal and/or
# scale the matrix
s.set_icntl(6, convert2int(gui.icntl6))
if gui.cntl1.lower() != 'default':
# relative threshold for numerical pivoting
s.set_cntl(1, convert2float(gui.cntl1))
if gui.cntl4.lower() != 'default':
# threshold for static pivoting
s.set_cntl(4, convert2float(gui.cntl4))
s.set_icntl(24, 0) # No Null detection
self.set_ordering_flag(s)
MPI.COMM_WORLD.Barrier()
if not gui.restore_fac:
if not self.silent:
dprint1("job1")
s.set_job(1)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job1) failed. Check error log"
if not self.silent:
dprint1("job2")
s.set_icntl(13, 0)
s.set_icntl(5, 0)
s.set_job(2)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job2) failed. Check error log"
if gui.write_fac:
if not self.silent:
dprint1("job7 (save)")
prefix, path = self.split_dir_prefix(gui.factor_path)
s.set_saveparam(prefix, path)
s.set_oocparam("ooc_", path)
# wait here to make sure path is created.
MPI.COMM_WORLD.Barrier()
s.set_job(7)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job7) failed. Check error log"
else:
if not self.silent:
dprint1("job8 (restore)")
pathes = gui.factor_path.split(',')
prefix, path = self.split_dir_prefix(pathes[ifactor].strip())
s.set_saveparam(prefix, path)
s.set_oocparam("ooc_", path)
MPI.COMM_WORLD.Barrier() # wait here to make sure path is created.
# s.set_job(-1)
# s.run()
s.set_job(8)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job8) failed. Check error log"
def SetOperator(self, A, dist, name=None):
try:
from mpi4py import MPI
except:
from petram.helper.dummy_mpi import MPI
myid = MPI.COMM_WORLD.rank
nproc = MPI.COMM_WORLD.size
from petram.ext.mumps.mumps_solve import i_array
gui = self.gui
s = self.s
if dist:
dprint1("SetOperator distributed matrix")
A.eliminate_zeros()
if gui.write_mat:
write_coo_matrix('matrix', A)
import petram.ext.mumps.mumps_solve as mumps_solve
dprint1('!!!these two must be consistent')
dprint1('sizeof(MUMPS_INT) ' , mumps_solve.SIZEOF_MUMPS_INT())
#dprint1('index data size ' , type(A.col[0]))
#dprint1('matrix data type ' , type(A.data[0]))
# set matrix format
s.set_icntl(5,0)
s.set_icntl(18,3)
dprint1("NNZ local: ", A.nnz)
nnz_array = np.array(MPI.COMM_WORLD.allgather(A.nnz))
if myid ==0:
dprint1("NNZ all: ", nnz_array, np.sum(nnz_array))
s.set_n(A.shape[1])
dtype_int = 'int'+str(mumps_solve.SIZEOF_MUMPS_INT()*8)
row = A.row
col = A.col
row = row.astype(dtype_int) + 1
col = col.astype(dtype_int) + 1
AA = self.make_matrix_entries(A)
if len(col) > 0:
dprint1('index data size ' , type(col[0]))
dprint1('matrix data type ' , type(AA[0]))
s.set_nz_loc(len(A.data))
s.set_irn_loc(i_array(row))
s.set_jcn_loc(i_array(col))
s.set_a_loc(self.data_array(AA))
s.set_icntl(2, 1)
self.dataset = (A.data, row, col)
else:
A = A.tocoo(False)#.astype('complex')
import petram.ext.mumps.mumps_solve as mumps_solve
dprint1('!!!these two must be consistent')
dprint1('sizeof(MUMPS_INT) ' , mumps_solve.SIZEOF_MUMPS_INT())
dtype_int = 'int'+str(mumps_solve.SIZEOF_MUMPS_INT()*8)
if gui.write_mat:
#tocsr().tocoo() forces the output is row sorted.
write_coo_matrix('matrix', A.tocsr().tocoo())
# No outputs
if myid ==0:
row = A.row
col = A.col
row = row.astype(dtype_int) + 1
col = col.astype(dtype_int) + 1
AA = self.make_matrix_entries(A)
if len(col) > 0:
dprint1('index data size ' , type(col[0]))
dprint1('matrix data type ' , type(AA[0]))
s.set_n(A.shape[0])
s.set_nz(len(A.data))
s.set_irn(i_array(row))
s.set_jcn(i_array(col))
s.set_a(self.data_array(AA))
self.dataset = (A.data, row, col)
# blr
if gui.use_blr:
s.set_icntl(35,1)
s.set_cntl(7, float(gui.blr_drop))
# out-of-core
if gui.out_of_core:
s.set_icntl(22, 1)
def convert2float(txt):
try:
return float(txt)
except:
assert False, "can not convert to float. Input text is "+txt
def convert2int(txt):
try:
return int(txt)
except:
assert False, "can not convert to float. Input text is "+txt
if gui.icntl14.lower() != 'default': # percentage increase in the estimated workingspace
s.set_icntl(14, convert2int(gui.icntl14))
if gui.icntl23.lower() != 'default': # maximum size of the working memory
s.set_icntl(23, convert2int(gui.icntl23))
if gui.icntl8.lower() != 'default': # the scaling strategy
s.set_icntl(8, convert2int(gui.icntl8))
if gui.icntl6.lower() != 'default': # permutes the matrix to azero-freediagonal and/or
s.set_icntl(6, convert2int(gui.icntl6)) # scale the matrix
if gui.icntl10.lower() != 'default': # iterative refinement
s.set_icntl(10, convert2int(gui.icntl10))
if gui.cntl1.lower() != 'default': # relative threshold for numerical pivoting
s.set_cntl(1, convert2float(gui.cntl1))
if gui.cntl4.lower() != 'default': # threshold for static pivoting
s.set_cntl(4, convert2float(gui.cntl4))
if gui.cntl2.lower() != 'default':
s.set_cntl(2, convert2float(gui.cntl2)) # stopping criterion for iterative refinement
self.set_ordering_flag(s)
MPI.COMM_WORLD.Barrier()
dprint1("job1")
s.set_job(1)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job1) faield. Check error log"
MPI.COMM_WORLD.Barrier()
dprint1("job2")
s.set_icntl(24, 1)
s.set_job(2)
s.run()
info1 = s.get_info(1)
if info1 != 0:
assert False, "MUMPS call (job2) faield. Check error log"