# Initialize state
global_state = numpy.zeros(global_width * global_height).reshape(
global_height, global_width)
global_state[[0, -1], :] = 1.0 # fill top and bottom row with 1.0
global_state[:, [0, -1]] = 0.5 # fill left and right column with 0.5
else:
global_state = []
epsilon = 0
if rank == 0:
datasize = global_height * global_width * global_state.dtype.itemsize
else:
datasize = -1
# All procs receive their local state and add empty ghost rows
epsilon = world.bcast(epsilon, root=0)
local_state = world.scatter(global_state, root=0)
height, width = local_state.shape
empty = numpy.zeros((1, width))
local_state = numpy.concatenate(
(empty, local_state, empty)) # add ghost rows top and bottom
if rank == 0:
print "Starting to solve for np:%i w:%i h:%i e:%s" % (
size, global_width, global_height, epsilon)
stencil_solver(local_state, epsilon)
pupy.finalize()
mpi = MPI()
world = mpi.MPI_COMM_WORLD
rank = world.rank()
size = world.size()
chunk_size = 4
iterations = 1000
data = [str(i) * chunk_size for i in range(size)]
#print "DATA:" + str(data)
recv_data = world.alltoall(data)
for i in xrange(iterations):
if rank == 0:
print "doing iteration %i of %i" % (i + 1, iterations)
recv_data = world.alltoall(data)
#if rank == 0:
# print "\tdata:%s \n\trecv_data:%s" % (data,recv_data)
#print "Rank:%i done (%i iterations)" %(rank,iterations)
expected_data = [str(rank) * chunk_size for _ in range(size)]
assert expected_data == recv_data
mpi.finalize()
def main(reps):
mpi = MPI()
world = mpi.MPI_COMM_WORLD
rank = world.rank()
size = world.size()
handle_list = []
obj = None # Will be replaced when calling a NBC.
if rank == 0:
print "Benchmarking with %d reps" % reps
datacount = 1000
while datacount % size != 0:
datacount += 1
data = range(datacount)
b = Benchmark(communicator=world, roots=range(size))
# Testing allgather
bw, _ = b.get_tester("allgather", datasize=rank)
for _ in range(reps):
with bw:
obj = world.iallgather(data)
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Testing barrier
bw, _ = b.get_tester("barrier", datasize=rank)
for _ in range(reps):
with bw:
obj = world.ibarrier()
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Testing bcast
bw, _ = b.get_tester("bcast", datasize=rank)
for _ in range(reps):
with bw:
obj = world.ibcast(data, root=0)
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Allreduce
bw, _ = b.get_tester("allreduce", datasize=rank)
for _ in range(reps):
with bw:
obj = world.iallreduce(data, MPI_sum)
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Alltoall
bw, _ = b.get_tester("alltoall", datasize=rank)
for _ in range(reps):
with bw:
obj = world.ialltoall(data)
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Gather
bw, _ = b.get_tester("gather", datasize=rank)
for _ in range(reps):
with bw:
obj = world.igather(data)
handle_list.append(obj)
world.waitall(handle_list)
world.barrier()
# Reduce
bw, _ = b.get_tester("reduce", datasize=rank)
for _ in range(reps):
with bw:
obj = world.ireduce(data, MPI_sum, 0)
handle_list.append(obj)
world.waitall(handle_list)
b.flush()
mpi.finalize()
