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‎projects/node_failure/grayscott_example.py‎

Lines changed: 117 additions & 106 deletions
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11
import numpy as np
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import pySDC.core.PFASST_stepwise as mp
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import pySDC.helpers.fault_tolerance as ft
4-
from pySDC.core.Stats import grep_stats
5-
from pySDC.core.datatype_classes.fenics_mesh import fenics_mesh
6-
from pySDC.core.sweeper_classes.generic_LU import generic_LU
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8-
from examples.fenics_grayscott.TransferClass import mesh_to_mesh_fenics
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from pySDC.core import CollocationClasses as collclass
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from pySDC.core import Log
11-
from pySDC.implementations.problem_classes.ProblemClass import fenics_grayscott
3+
import projects.node_failure.emulate_hard_faults as ft
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from projects.node_failure.allinclusive_classic_nonMPI_hard_faults import allinclusive_classic_nonMPI_hard_faults
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from pySDC.helpers.stats_helper import filter_stats, sort_stats
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from pySDC.implementations.collocation_classes.gauss_radau_right import CollGaussRadau_Right
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from pySDC.implementations.sweeper_classes.generic_LU import generic_LU
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from pySDC.implementations.datatype_classes.fenics_mesh import fenics_mesh
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from pySDC.implementations.transfer_classes.TransferFenicsMesh import mesh_to_mesh_fenics
10+
from pySDC.implementations.problem_classes.GrayScott_1D_FEniCS_implicit import fenics_grayscott
1211

1312

14-
if __name__ == "__main__":
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16-
# set global logger (remove this if you do not want the output at all)
17-
logger = Log.setup_custom_logger('root')
13+
# noinspection PyShadowingNames,PyShadowingBuiltins
14+
def main(ft_strategies):
15+
"""
16+
This routine generates the heatmaps showing the residual for node failures at different steps and iterations
17+
"""
1818

1919
num_procs = 32
2020

21-
# assert num_procs == 1,'turn on predictor!'
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23-
# This comes as read-in for the level class
24-
lparams = {}
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lparams['restol'] = 1E-07
26-
27-
sparams = {}
28-
sparams['maxiter'] = 50
29-
sparams['fine_comm'] = True
30-
31-
# This comes as read-in for the problem class
32-
pparams = {}
33-
# pparams['Du'] = 1.0
34-
# pparams['Dv'] = 0.01
35-
# pparams['A'] = 0.01
36-
# pparams['B'] = 0.10
21+
# setup parameters "in time"
22+
t0 = 0
23+
dt = 2.0
24+
Tend = 1280.0
25+
Nsteps = int((Tend-t0)/dt)
26+
27+
# initialize level parameters
28+
level_params = dict()
29+
level_params['restol'] = 1E-07
30+
level_params['dt'] = dt
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32+
# initialize step parameters
33+
step_params = dict()
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step_params['maxiter'] = 50
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36+
# initialize space transfer parameters
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space_transfer_params = dict()
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space_transfer_params['finter'] = True
39+
40+
# initialize sweeper parameters
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sweeper_params = dict()
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sweeper_params['collocation_class'] = CollGaussRadau_Right
43+
sweeper_params['num_nodes'] = [3]
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sweeper_params['QI'] = 'LU'
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46+
# initialize controller parameters
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controller_params = dict()
48+
controller_params['logger_level'] = 20
49+
50+
# initialize problem parameters
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problem_params = dict()
52+
# problem_params['Du'] = 1.0
53+
# problem_params['Dv'] = 0.01
54+
# problem_params['A'] = 0.01
55+
# problem_params['B'] = 0.10
3756
# splitting pulses until steady state
38-
# pparams['Du'] = 1.0
39-
# pparams['Dv'] = 0.01
40-
# pparams['A'] = 0.02
41-
# pparams['B'] = 0.079
57+
# problem_params['Du'] = 1.0
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# problem_params['Dv'] = 0.01
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# problem_params['A'] = 0.02
60+
# problem_params['B'] = 0.079
4261
# splitting pulses until steady state
43-
pparams['Du'] = 1.0
44-
pparams['Dv'] = 0.01
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pparams['A'] = 0.09
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pparams['B'] = 0.086
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48-
pparams['t0'] = 0.0 # ugly, but necessary to set up ProblemClass
49-
# pparams['c_nvars'] = [(16,16)]
50-
pparams['c_nvars'] = [512]
51-
pparams['family'] = 'CG'
52-
pparams['order'] = [4]
53-
pparams['refinements'] = [1,0]
54-
55-
56-
# This comes as read-in for the transfer operations
57-
tparams = {}
58-
tparams['finter'] = True
59-
60-
# Fill description dictionary for easy hierarchy creation
61-
description = {}
62-
description['problem_class'] = fenics_grayscott
63-
description['problem_params'] = pparams
64-
description['dtype_u'] = fenics_mesh
65-
description['dtype_f'] = fenics_mesh
66-
description['collocation_class'] = collclass.CollGaussRadau_Right
67-
description['num_nodes'] = 3
68-
description['sweeper_class'] = generic_LU
69-
description['level_params'] = lparams
70-
description['transfer_class'] = mesh_to_mesh_fenics
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description['transfer_params'] = tparams
72-
# description['hook_class'] = fenics_output
62+
problem_params['Du'] = 1.0
63+
problem_params['Dv'] = 0.01
64+
problem_params['A'] = 0.09
65+
problem_params['B'] = 0.086
66+
67+
problem_params['t0'] = t0 # ugly, but necessary to set up ProblemClass
68+
problem_params['c_nvars'] = [256]
69+
problem_params['family'] = 'CG'
70+
problem_params['order'] = [4]
71+
problem_params['refinements'] = [1, 0]
72+
73+
# fill description dictionary for easy step instantiation
74+
description = dict()
75+
description['problem_class'] = fenics_grayscott # pass problem class
76+
description['problem_params'] = problem_params # pass problem parameters
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description['dtype_u'] = fenics_mesh # pass data type for u
78+
description['dtype_f'] = fenics_mesh # pass data type for f
79+
description['sweeper_class'] = generic_LU # pass sweeper (see part B)
80+
description['sweeper_params'] = sweeper_params # pass sweeper parameters
81+
description['level_params'] = level_params # pass level parameters
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description['step_params'] = step_params # pass step parameters
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description['space_transfer_class'] = mesh_to_mesh_fenics # pass spatial transfer class
84+
description['space_transfer_params'] = space_transfer_params # pass paramters for spatial transfer
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7486
ft.hard_random = 0.03
7587

76-
# strategies = ['NOFAULT']
77-
# strategies = ['SPREAD','INTERP','INTERP_PREDICT','SPREAD_PREDICT']
78-
strategies = ['INTERP', 'INTERP_PREDICT']
88+
controller = allinclusive_classic_nonMPI_hard_faults(num_procs=num_procs,
89+
controller_params=controller_params,
90+
description=description)
91+
92+
# get initial values on finest level
93+
P = controller.MS[0].levels[0].prob
94+
uinit = P.u_exact(t0)
7995

80-
for strategy in strategies:
96+
for strategy in ft_strategies:
8197

82-
print('------------------------------------------ working on strategy ',strategy)
98+
print('------------------------------------------ working on strategy ', strategy)
8399
ft.strategy = strategy
84100

85101
# read in reference data from clean run, will provide reproducable locations for faults
86-
if not strategy is 'NOFAULT':
87-
reffile = np.load('PFASST_GRAYSCOTT_stats_hf_NOFAULT_P32.npz')
102+
if strategy is not 'NOFAULT':
103+
reffile = np.load('data/PFASST_GRAYSCOTT_stats_hf_NOFAULT_P16.npz')
88104
ft.refdata = reffile['hard_stats']
89105

90-
# quickly generate block of steps
91-
MS = mp.generate_steps(num_procs,sparams,description)
92-
93-
# setup parameters "in time"
94-
t0 = MS[0].levels[0].prob.t0
95-
dt = 2.0
96-
Tend = 1280.0
97-
98-
# get initial values on finest level
99-
P = MS[0].levels[0].prob
100-
uinit = P.u_exact(t0)
101-
102106
# call main function to get things done...
103-
uend,stats = mp.run_pfasst(MS,u0=uinit,t0=t0,dt=dt,Tend=Tend)
107+
uend, stats = controller.run(u0=uinit, t0=t0, Tend=Tend)
104108

105-
# stats magic: get all residuals
106-
extract_stats = grep_stats(stats,level=-1,type='residual')
109+
# get residuals of the run
110+
extract_stats = filter_stats(stats, type='residual_post_iteration')
107111

108-
# find boundaries
109-
maxsteps = 0
112+
# find boundaries for x-,y- and c-axis as well as arrays
113+
maxprocs = 0
110114
maxiter = 0
111115
minres = 0
112116
maxres = -99
113-
for k,v in extract_stats.items():
114-
maxsteps = max(maxsteps,getattr(k,'step'))
115-
maxiter = max(maxiter,getattr(k,'iter'))
116-
minres = min(minres,np.log10(v))
117-
maxres = max(maxres,np.log10(v))
118-
119-
# fill residual array
120-
residual = np.zeros((maxiter,maxsteps+1))
121-
residual[:] = 0
122-
for k,v in extract_stats.items():
123-
step = getattr(k,'step')
124-
iter = getattr(k,'iter')
117+
for k, v in extract_stats.items():
118+
maxprocs = max(maxprocs, getattr(k, 'process'))
119+
maxiter = max(maxiter, getattr(k, 'iter'))
120+
minres = min(minres, np.log10(v))
121+
maxres = max(maxres, np.log10(v))
122+
123+
# grep residuals and put into array
124+
residual = np.zeros((maxiter, maxprocs + 1))
125+
residual[:] = -99
126+
for k, v in extract_stats.items():
127+
step = getattr(k, 'process')
128+
iter = getattr(k, 'iter')
125129
if iter is not -1:
126-
residual[iter-1,step] = v
130+
residual[iter - 1, step] = np.log10(v)
127131

128132
# stats magic: get niter (probably redundant with maxiter)
129-
extract_stats = grep_stats(stats,iter=-1,type='niter')
130-
iter_count = np.zeros(maxsteps+1)
131-
for k,v in extract_stats.items():
132-
step = getattr(k,'step')
133-
iter_count[step] = v
133+
extract_stats = filter_stats(stats, level=-1, type='niter')
134+
sortedlist_stats = sort_stats(extract_stats, sortby='process')
135+
iter_count = np.zeros(Nsteps)
136+
for item in sortedlist_stats:
137+
iter_count[item[0]] = item[1]
134138
print(iter_count)
135139

136-
np.savez('PFASST_GRAYSCOTT_stats_hf_'+ft.strategy+'_P'+str(num_procs)+'_cN512',residual=residual,iter_count=iter_count,hard_stats=ft.hard_stats)
140+
np.savez('data/PFASST_GRAYSCOTT_stats_hf_' + ft.strategy + '_P' + str(num_procs), residual=residual,
141+
iter_count=iter_count, hard_stats=ft.hard_stats)
142+
143+
144+
if __name__ == "__main__":
145+
# ft_strategies = ['SPREAD', 'SPREAD_PREDICT', 'INTERP', 'INTERP_PREDICT']
146+
ft_strategies = ['NOFAULT']
137147

148+
main(ft_strategies=ft_strategies)

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