def create_pcd_solver(comm, pcd_variant, ls, mumps_debug=False):
prefix = "NS_"
# Set up linear solver (GMRES with right preconditioning using Schur fact)
linear_solver = PCDKrylovSolver(comm=comm)
linear_solver.set_options_prefix(prefix)
linear_solver.parameters["relative_tolerance"] = 1e-6
PETScOptions.set(prefix + "ksp_gmres_restart", 150)
# Set up subsolvers
PETScOptions.set(prefix + "fieldsplit_p_pc_python_type",
"fenapack.PCDRPC_" + pcd_variant)
if ls == "iterative":
PETScOptions.set(prefix + "fieldsplit_u_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_u_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_u_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_u_pc_hypre_type", "boomeramg")
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_P_max", 4)
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_agg_nl", 1)
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_agg_num_paths", 2)
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_coarsen_type", "HMIS")
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_interp_type", "ext+i")
# PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_boomeramg_no_CF")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_pc_type",
"hypre") # "gamg"
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_pc_hypre_type",
"boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_type",
"hypre") # "gamg"
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_hypre_type",
"boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_type", "chebyshev")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_max_it", 5)
PETScOptions.set(
prefix + "fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues",
"0.5, 2.0")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_pc_type", "jacobi")
elif ls == "direct":
# Debugging MUMPS
if mumps_debug:
PETScOptions.set(prefix + "fieldsplit_u_mat_mumps_icntl_4", 2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_mat_mumps_icntl_4",
2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_mat_mumps_icntl_4",
2)
else:
assert False
# Apply options
linear_solver.set_from_options()
return linear_solver
def create_pcd_solver(comm, pcd_variant, ls, mumps_debug=False):
prefix = ""
# Set up linear solver (GMRES with right preconditioning using Schur fact)
linear_solver = PCDKrylovSolver(comm=comm)
linear_solver.set_options_prefix(prefix)
linear_solver.parameters["relative_tolerance"] = 1e-6
PETScOptions.set(prefix + "ksp_gmres_restart", 150)
# Set up subsolvers
PETScOptions.set(prefix + "fieldsplit_p_pc_python_type",
"fenapack.PCDRPC_" + pcd_variant)
if ls == "iterative":
PETScOptions.set(prefix + "fieldsplit_u_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_u_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_u_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_u_pc_hypre_type", "boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Rp_pc_hypre_type",
"boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_hypre_type",
"boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_type", "chebyshev")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_max_it", 5)
PETScOptions.set(
prefix + "fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues",
"0.5, 2.0")
# CHANGE #0: The above estimate is valid only for P1 pressure.
# Increase upper bound for higher OPA!
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_pc_type", "jacobi")
elif ls == "direct":
# Debugging MUMPS
if mumps_debug:
PETScOptions.set(prefix + "fieldsplit_u_mat_mumps_icntl_4", 2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_mat_mumps_icntl_4",
2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_mat_mumps_icntl_4",
2)
else:
assert False
# Apply options
linear_solver.set_from_options()
return linear_solver
def create_solver(comm, pcd_variant, ls, mumps_debug=False):
prefix = "s" + get_random_string() + "_"
# Set up linear solver (GMRES with right preconditioning using Schur fact)
linear_solver = PCDKrylovSolver(comm=comm)
linear_solver.set_options_prefix(prefix)
linear_solver.parameters["relative_tolerance"] = 1e-6
PETScOptions.set(prefix + "ksp_gmres_restart", 150)
# Set up subsolvers
PETScOptions.set(prefix + "fieldsplit_p_pc_python_type",
"fenapack.PCDPC_" + pcd_variant)
if ls == "iterative":
PETScOptions.set(prefix + "fieldsplit_u_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_u_ksp_max_it", 1)
PETScOptions.set(prefix + "fieldsplit_u_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_u_pc_hypre_type", "boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_type", "richardson")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_ksp_max_it", 2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_type", "hypre")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_pc_hypre_type",
"boomeramg")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_type", "chebyshev")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_ksp_max_it", 5)
PETScOptions.set(
prefix + "fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues",
"0.5, 2.0")
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_pc_type", "jacobi")
elif ls == "direct":
# Debugging MUMPS
if mumps_debug:
PETScOptions.set(prefix + "fieldsplit_u_mat_mumps_icntl_4", 2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Ap_mat_mumps_icntl_4",
2)
PETScOptions.set(prefix + "fieldsplit_p_PCD_Mp_mat_mumps_icntl_4",
2)
else:
assert False
# Apply options
linear_solver.set_from_options()
# Set up nonlinear solver
solver = PCDNewtonSolver(linear_solver)
solver.parameters["relative_tolerance"] = 1e-5
return solver
def create_solver(comm, pcd_variant, ls, mumps_debug=False):
prefix = "s" + get_random_string() + "_"
# Set up linear solver (GMRES with right preconditioning using Schur fact)
linear_solver = PCDKrylovSolver(comm=comm)
linear_solver.set_options_prefix(prefix)
linear_solver.parameters["relative_tolerance"] = 1e-6
PETScOptions.set(prefix+"ksp_gmres_restart", 150)
# Set up subsolvers
PETScOptions.set(prefix+"fieldsplit_p_pc_python_type", "fenapack.PCDPC_" + pcd_variant)
if ls == "iterative":
PETScOptions.set(prefix+"fieldsplit_u_ksp_type", "richardson")
PETScOptions.set(prefix+"fieldsplit_u_ksp_max_it", 1)
PETScOptions.set(prefix+"fieldsplit_u_pc_type", "hypre")
PETScOptions.set(prefix+"fieldsplit_u_pc_hypre_type", "boomeramg")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Ap_ksp_type", "richardson")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Ap_ksp_max_it", 2)
PETScOptions.set(prefix+"fieldsplit_p_PCD_Ap_pc_type", "hypre")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Ap_pc_hypre_type", "boomeramg")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Mp_ksp_type", "chebyshev")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Mp_ksp_max_it", 5)
PETScOptions.set(prefix+"fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues", "0.5, 2.0")
PETScOptions.set(prefix+"fieldsplit_p_PCD_Mp_pc_type", "jacobi")
elif ls == "direct":
# Debugging MUMPS
if mumps_debug:
PETScOptions.set(prefix+"fieldsplit_u_mat_mumps_icntl_4", 2)
PETScOptions.set(prefix+"fieldsplit_p_PCD_Ap_mat_mumps_icntl_4", 2)
PETScOptions.set(prefix+"fieldsplit_p_PCD_Mp_mat_mumps_icntl_4", 2)
else:
assert False
# Apply options
linear_solver.set_from_options()
# Set up nonlinear solver
solver = PCDNewtonSolver(linear_solver)
solver.parameters["relative_tolerance"] = 1e-5
return solver
PETScOptions.set("fieldsplit_u_ksp_max_it", 1)
PETScOptions.set("fieldsplit_u_pc_type", "hypre")
PETScOptions.set("fieldsplit_u_pc_hypre_type", "boomeramg")
PETScOptions.set("fieldsplit_p_PCD_Ap_ksp_type", "gmres")
PETScOptions.set("fieldsplit_p_PCD_Ap_ksp_max_it", 2)
PETScOptions.set("fieldsplit_p_PCD_Ap_pc_type", "hypre")
PETScOptions.set("fieldsplit_p_PCD_Ap_pc_hypre_type", "boomeramg")
PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_type", "gmres")
PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_max_it", 5)
#PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues", "0.5, 2.0")
#PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_chebyshev_esteig", "1,0,0,1") # FIXME: What does it do?
PETScOptions.set("fieldsplit_p_PCD_Mp_pc_type", "hypre")
PETScOptions.set("fieldsplit_p_PCD_Mp_pc_hypre_type", "boomeramg")
# Apply options
linear_solver.set_from_options()
# Set up nonlinear solver
solver = PCDNewtonSolver(linear_solver)
#solver.parameters["relative_tolerance"] = 1e-7
# Solve problem
solver.solve(problem, w.vector())
assign(u_c,w.sub(0))
diff = (u_c.vector().get_local() - u_.vector().get_local())
picard_error = np.linalg.norm(diff, ord = np.Inf)
assign(u_,w.sub(0))
print ('error', picard_error, ' iter = ', picard_iter)
# Report timings
#list_timings(TimingClear.clear, [TimingType.wall, TimingType.user])
PETScOptions.set("fieldsplit_p_PCD_Ap_ksp_max_it", 2)
PETScOptions.set("fieldsplit_p_PCD_Ap_pc_type", "hypre")
PETScOptions.set("fieldsplit_p_PCD_Ap_pc_hypre_type", "boomeramg")
PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_type", "chebyshev")
PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_max_it", 5)
PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_chebyshev_eigenvalues", "0.5, 2.0")
#PETScOptions.set("fieldsplit_p_PCD_Mp_ksp_chebyshev_esteig", "1,0,0,1") # FIXME: What does it do?
PETScOptions.set("fieldsplit_p_PCD_Mp_pc_type", "jacobi")
elif args.ls == "direct" and args.mumps_debug:
# Debugging MUMPS
PETScOptions.set("fieldsplit_u_mat_mumps_icntl_4", 2)
PETScOptions.set("fieldsplit_p_PCD_Ap_mat_mumps_icntl_4", 2)
PETScOptions.set("fieldsplit_p_PCD_Mp_mat_mumps_icntl_4", 2)
# Apply options
linear_solver.set_from_options()
# Set up nonlinear solver
solver = PCDNewtonSolver(linear_solver)
solver.parameters["relative_tolerance"] = 1e-5
# Solve problem
t = 0.0
time_iters = 0
krylov_iters = 0
solution_time = 0.0
while t < args.t_end and not near(t, args.t_end, 0.1*args.dt):
# Move to current time level
t += args.dt
time_iters += 1