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import os
import numpy as np
import pyopencl as cl
from grudge import sym, bind, DGDiscretizationWithBoundaries
from grudge.shortcuts import set_up_rk4
def simple_wave_entrypoint(dim=2, num_elems=256, order=4, num_steps=30,
log_filename="grudge.dat"):
cl_ctx = cl.create_some_context()
queue = cl.CommandQueue(cl_ctx)
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_parts = comm.Get_size()
n = int(num_elems ** (1./dim))
from meshmode.distributed import MPIMeshDistributor
mesh_dist = MPIMeshDistributor(comm)
if mesh_dist.is_mananger_rank():
from meshmode.mesh.generation import generate_regular_rect_mesh
mesh = generate_regular_rect_mesh(a=(-0.5,)*dim,
b=(0.5,)*dim,
n=(n,)*dim)
from pymetis import part_graph
_, p = part_graph(num_parts,
xadj=mesh.nodal_adjacency.neighbors_starts.tolist(),
adjncy=mesh.nodal_adjacency.neighbors.tolist())
part_per_element = np.array(p)
local_mesh = mesh_dist.send_mesh_parts(mesh, part_per_element, num_parts)
else:
local_mesh = mesh_dist.receive_mesh_part()
vol_discr = DGDiscretizationWithBoundaries(cl_ctx, local_mesh, order=order,
mpi_communicator=comm)
source_center = np.array([0.1, 0.22, 0.33])[:local_mesh.dim]
source_width = 0.05
source_omega = 3
sym_x = sym.nodes(local_mesh.dim)
sym_source_center_dist = sym_x - source_center
sym_t = sym.ScalarVariable("t")
from grudge.models.wave import StrongWaveOperator
from meshmode.mesh import BTAG_ALL, BTAG_NONE
op = StrongWaveOperator(-0.1, vol_discr.dim,
source_f=(
sym.sin(source_omega*sym_t)
* sym.exp(
-np.dot(sym_source_center_dist, sym_source_center_dist)
/ source_width**2)),
dirichlet_tag=BTAG_NONE,
neumann_tag=BTAG_NONE,
radiation_tag=BTAG_ALL,
flux_type="upwind")
from pytools.obj_array import join_fields
fields = join_fields(vol_discr.zeros(queue),
[vol_discr.zeros(queue) for i in range(vol_discr.dim)])
from pytools.log import LogManager, \
add_general_quantities, \
add_run_info, \
IntervalTimer, EventCounter
# NOTE: LogManager hangs when using a file on a shared directory.
logmgr = LogManager(log_filename, "w", comm)
add_run_info(logmgr)
add_general_quantities(logmgr)
log_quantities =\
{"rank_data_swap_timer": IntervalTimer("rank_data_swap_timer",
"Time spent evaluating RankDataSwapAssign"),
"rank_data_swap_counter": EventCounter("rank_data_swap_counter",
"Number of RankDataSwapAssign instructions evaluated"),
"exec_timer": IntervalTimer("exec_timer",
"Total time spent executing instructions"),
"insn_eval_timer": IntervalTimer("insn_eval_timer",
"Time spend evaluating instructions"),
"future_eval_timer": IntervalTimer("future_eval_timer",
"Time spent evaluating futures"),
"busy_wait_timer": IntervalTimer("busy_wait_timer",
"Time wasted doing busy wait")}
for quantity in log_quantities.values():
logmgr.add_quantity(quantity)
bound_op = bind(vol_discr, op.sym_operator())
def rhs(t, w):
val, rhs.profile_data = bound_op(queue, profile_data=rhs.profile_data,
log_quantities=log_quantities,
t=t, w=w)
return val
rhs.profile_data = {}
dt = 0.04
dt_stepper = set_up_rk4("w", dt, fields, rhs)
logmgr.tick_before()
for event in dt_stepper.run(t_end=dt * num_steps):
if isinstance(event, dt_stepper.StateComputed):
logmgr.tick_after()
logmgr.tick_before()
logmgr.tick_after()
def print_profile_data(data):
print("""execute() for rank %d:
\tInstruction Evaluation: %f%%
\tFuture Evaluation: %f%%
\tBusy Wait: %f%%
\tTotal: %f seconds""" %
(comm.Get_rank(),
data['insn_eval_time'] / data['total_time'] * 100,
data['future_eval_time'] / data['total_time'] * 100,
data['busy_wait_time'] / data['total_time'] * 100,
data['total_time']))
print_profile_data(rhs.profile_data)
logmgr.close()
if __name__ == "__main__":
assert "RUN_WITHIN_MPI" in os.environ, "Must run within mpi"
import sys
assert len(sys.argv) == 5, \
"Usage: %s %s num_elems order num_steps logfile" \
% (sys.executable, sys.argv[0])
simple_wave_entrypoint(num_elems=int(sys.argv[1]),
order=int(sys.argv[2]),
num_steps=int(sys.argv[3]),
log_filename=sys.argv[4])