def collect_timings(outdir, tic):
# list_timings(TimingClear.keep, [TimingType.wall, TimingType.system])
# t = timings(TimingClear.keep, [TimingType.wall, TimingType.user, TimingType.system])
t = timings(TimingClear.keep, [TimingType.wall])
# Use different MPI reductions
t_sum = MPI.sum(MPI.comm_world, t)
# t_min = MPI.min(MPI.comm_world, t)
# t_max = MPI.max(MPI.comm_world, t)
t_avg = MPI.avg(MPI.comm_world, t)
# Print aggregate timings to screen
print('\n' + t_sum.str(True))
# print('\n'+t_min.str(True))
# print('\n'+t_max.str(True))
print('\n' + t_avg.str(True))
# Store to XML file on rank 0
if MPI.rank(MPI.comm_world) == 0:
f = File(MPI.comm_self, os.path.join(outdir, "timings_aggregate.xml"))
f << t_sum
# f << t_min
# f << t_max
f << t_avg
dump_timings_to_xml(os.path.join(outdir, "timings_avg_min_max.xml"),
TimingClear.clear)
elapsed = time.time() - tic
comm = mpi4py.MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
if rank == 0:
with open(os.path.join(outdir, 'timings.pkl'), 'w') as f:
json.dump({'elapsed': elapsed, 'size': size}, f)
pass
(fig2, ax1, ax2) = pp.plot_spectrum(parameters, data, tc)
plt.legend(loc='lower left')
# ax2.set_ylim(-1e-7, 2e-4)
fig2.savefig(os.path.join(experiment, "spectrum.pdf"),
bbox_inches='tight')
from dolfin import list_timings, TimingType, TimingClear
list_timings(TimingClear.keep, [TimingType.wall, TimingType.system])
t = list_timings(TimingClear.keep,
[TimingType.wall, TimingType.user, TimingType.system])
# Use different MPI reductions
# t_sum = MPI.sum(MPI.comm_world, t[0])
# t_min = MPI.min(MPI.comm_world, t[1])
# t_max = MPI.max(MPI.comm_world, t[2])
t_avg = MPI.avg(MPI.comm_world, t[3])
# Print aggregate timings to screen
# print('\n'+t_sum.str(True))
# print('\n'+t_min.str(True))
# print('\n'+t_max.str(True))
print('\n' + t_avg.str(True))
# Store to XML file on rank 0
if MPI.rank(MPI.comm_world) == 0:
f = File(MPI.comm_self,
os.path.join(experiment, "timings_aggregate.xml"))
# f << t_sum
# f << t_min
# f << t_max
f << t_avg