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rb-weak-scale.py
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rb-weak-scale.py
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from argparse import ArgumentParser
import os
import cPickle
import pandas
from collections import defaultdict
import problem.rayleigh_benard as module
from firedrake import COMM_WORLD, parameters
from firedrake.petsc import PETSc
from mpi4py import MPI
parameters["pyop2_options"]["lazy_evaluation"] = False
parser = ArgumentParser(description="""Profile solves""", add_help=False)
parser.add_argument("--results-file", action="store", default="solve-timings.csv",
help="Where to put the results")
parser.add_argument("--overwrite", action="store_true", default=False,
help="Overwrite existing output? Default is to append.")
parser.add_argument("--parameters", default=None, action="store",
help="Select specific parameter set?")
parser.add_argument("--help", action="store_true",
help="Show help")
args, _ = parser.parse_known_args()
if args.help:
help = parser.format_help()
PETSc.Sys.Print("%s\n" % help)
problem_cls = module.Problem
if args.parameters is not None:
if args.parameters not in problem_cls.parameter_names:
raise ValueError("Unrecognised parameter '%s', not in %s", args.parameters,
problem_cls.parameter_names)
parameter_names = [args.parameters]
else:
parameter_names = problem_cls.parameter_names
results = os.path.abspath(args.results_file)
warm = defaultdict(bool)
PETSc.Log.begin()
def run_solve(problem_cls, degree):
target_mesh_size = {24: (20, 1),
48: (25, 1),
96: (32, 1),
192: (40, 1),
384: (50, 1),
768: (64, 1),
1536: (80, 1),
3072: (100, 1),
6144: (125, 1),
12288: (160, 1)}
size, ref = target_mesh_size[COMM_WORLD.size]
problem = problem_cls(degree=degree, N=size, refinements=ref)
first = True
for name in parameter_names:
parameters = getattr(problem, name)
solver = problem.solver(parameters=parameters)
PETSc.Sys.Print("\nSolving with parameter set %s, %s, %s..." % (name, problem.N, problem.degree))
if not warm[(name, degree)]:
PETSc.Sys.Print("Warmup solve")
problem.u.assign(0)
with PETSc.Log.Stage("Warmup"):
try:
solver.solve()
except:
PETSc.Sys.Print("Unable to solve %s, %s, %s" % (name, problem.N, problem.degree))
PETSc.Sys.Print("************************************")
import traceback
PETSc.Sys.Print(*traceback.format_stack())
PETSc.Sys.Print("************************************")
raise
warm[(name, degree)] = True
problem.u.assign(0)
PETSc.Sys.Print("Timed solve")
solver.snes.setConvergenceHistory()
solver.snes.ksp.setConvergenceHistory()
with PETSc.Log.Stage("P(%d, %d) Warm solve %s" % (degree, size, name)):
try:
solver.solve()
snes = PETSc.Log.Event("SNESSolve").getPerfInfo()
ksp = PETSc.Log.Event("KSPSolve").getPerfInfo()
pcsetup = PETSc.Log.Event("PCSetUp").getPerfInfo()
pcapply = PETSc.Log.Event("PCApply").getPerfInfo()
jac = PETSc.Log.Event("SNESJacobianEval").getPerfInfo()
residual = PETSc.Log.Event("SNESFunctionEval").getPerfInfo()
snes_time = problem.comm.allreduce(snes["time"], op=MPI.SUM) / problem.comm.size
jac_time = problem.comm.allreduce(jac["time"], op=MPI.SUM) / problem.comm.size
residual_time = problem.comm.allreduce(residual["time"], op=MPI.SUM) / problem.comm.size
ksp_time = problem.comm.allreduce(ksp["time"], op=MPI.SUM) / problem.comm.size
pcsetup_time = problem.comm.allreduce(pcsetup["time"], op=MPI.SUM) / problem.comm.size
pcapply_time = problem.comm.allreduce(pcapply["time"], op=MPI.SUM) / problem.comm.size
newton_its = solver.snes.getIterationNumber()
ksp_its = solver.snes.getLinearSolveIterations()
num_cells = problem.comm.allreduce(problem.mesh.cell_set.size, op=MPI.SUM)
if COMM_WORLD.rank == 0:
if not os.path.exists(os.path.dirname(results)):
os.makedirs(os.path.dirname(results))
if args.overwrite:
if first:
mode = "w"
header = True
else:
mode = "a"
header = False
first = False
else:
mode = "a"
header = not os.path.exists(results)
snes_history, linear_its = solver.snes.getConvergenceHistory()
ksp_history = solver.snes.ksp.getConvergenceHistory()
data = {"snes_its": newton_its,
"ksp_its": ksp_its,
"snes_history": cPickle.dumps(snes_history),
"linear_its": cPickle.dumps(linear_its),
"ksp_history": cPickle.dumps(ksp_history),
"SNESSolve": snes_time,
"KSPSolve": ksp_time,
"PCSetUp": pcsetup_time,
"PCApply": pcapply_time,
"JacobianEval": jac_time,
"FunctionEval": residual_time,
"num_processes": problem.comm.size,
"mesh_size": size * (2**ref),
"num_cells": num_cells,
"dimension": problem.dimension,
"degree": problem.degree,
"solver_parameters": cPickle.dumps(solver.parameters),
"parameter_name": name,
"dofs": problem.u.dof_dset.layout_vec.getSize(),
"name": problem.name}
df = pandas.DataFrame(data, index=[0])
df.to_csv(results, index=False, mode=mode, header=header)
except:
PETSc.Sys.Print("Unable to solve %s, %s, %s" % (name, problem.N, problem.degree))
PETSc.Sys.Print("************************************")
import traceback
PETSc.Sys.Print(*traceback.format_stack())
PETSc.Sys.Print("************************************")
raise
PETSc.Sys.Print("Solving with parameter set %s, %s, %s...done" % (name, problem.N, problem.degree))
run_solve(problem_cls, 1)