def worker(current_rank, num_ranks, and_lco):
target_rank = (current_rank + 1) % num_ranks
array = np.empty((128//NUM_TRY, 1024, 1024))
finish_copy = hpx.Future()
some_marshalled_action(hpx.THERE(target_rank), array, sync='async', lsync_lco=finish_copy, rsync_lco=and_lco)
finish_copy.wait()
print("worker {0} sends {1} bytes".format(current_rank, array.nbytes))
return hpx.SUCCESS
def main():
start = hpx.time_now()
num_ranks = hpx.get_num_ranks()
and_lco = hpx.And(num_ranks)
for i in range(num_ranks):
worker(hpx.THERE(i), i, num_ranks, rsync_lco=and_lco)
and_lco.wait()
print(hpx.time_elapsed_ms(start))
hpx.exit()
def create_node(low, high):
# this function returns a GlobalMemory object for the created node
where = map_bound_to_locality(low, high)
rtv = hpx.GlobalMemory.alloc_local_at(1, 1, node_type, hpx.THERE(where))
vals = np.array(
[(hpx.NULL().addr, hpx.NULL().addr, low, high,
np.array([(0.0, 0.0, 0.0)], dtype=moment_type), hpx.NULL().addr, 0)],
dtype=node_type)
rtv[0].set(vals)
return rtv
def main():
num_ranks = hpx.get_num_ranks()
print(num_ranks)
array = hpx.GlobalMemory.alloc_cyclic(num_ranks, (64, 1024, 1024),
dtype=np.dtype(float))
start = hpx.time_now()
and_lco = hpx.And(num_ranks)
for i in range(num_ranks):
copy_from_array(hpx.THERE(i), array, i, num_ranks, rsync_lco=and_lco)
and_lco.wait()
print(hpx.time_elapsed_ms(start))
hpx.exit()
def main_action():
num_node = hpx.get_num_ranks()
print("program runs on {0} nodes".format(num_node))
step_size = (high - low) / total_cells
cell_per_node = total_cells // num_node
result_lco = hpx.Reduce(num_node, (1, ), np.dtype(float), result_init,
result_op)
for i in range(num_node):
calculate_integral(hpx.THERE(i), low + i * step_size * cell_per_node,
step_size, cell_per_node, result_lco)
print(result_lco.get())
print(fint(high) - fint(low))
hpx.exit()
def worker(current_rank, num_ranks):
target_rank = (current_rank + 1) % num_ranks
array = np.array((128, 1024, 1024))
some_marshalled_action(hpx.THERE(target_rank), array, sync='rsync')
print("worker {0} sends {1} bytes".format(current_rank, array.nbytes))
return hpx.SUCCESS