g = GaussSolver(np.array(rows), comm, n)
res = g.calc()
print(formatting(comm.rank, format_action('result', rows=res)))
for proc in range(1, comm.size):
res += comm.recv(source=proc)
res.sort(key=lambda row: row[-1])
x = []
for row in res:
x.append(row[0])
totalTimer.finish()
print(formatting(comm.rank, format_action('result')))
write_vector(x, out)
print(formatting(comm.rank, format_action('answer', x=x)))
else:
procTimer = Timer('proc{}'.format(comm.rank))
n = comm.bcast(None, root=MASTER)
step = n // comm.size
if not step:
sys.exit()
)
square = ProcSquare(
full_region=Region(right=cols, bottom=rows),
region=region,
left_top=point,
step_x=step_x,
step_y=step_y
)
print formatting(comm.rank, '\n$\tcoord:\t{0}\n$\tregion:\t{1}\n$\tpoint:\t{2}'.format(coords, region, point))
cart_comm.barrier()
iterations = 0
if comm.rank == master:
t_init.finish(comm.rank)
t_calc = Timer('calculation')
while min_diff > epsilon:
square.exch(cart_comm)
square.calc()
diff = square.diff
iterations += 1
min_diff = cart_comm.allreduce(diff, op=MPI.MAX)
if comm.rank == master:
t_calc.finish(master)
t_calc = Timer('collecting results')
results = []
for i in range(rows):
for i in range(step):
comm.send(A[cur + i] + [cur + i],
dest=proc) # send row with index as last element
cur += step
inversed = _do_inversion(comm, rows)
A_inv = inversed
for proc in range(1, comm.size):
A_inv += comm.recv(source=proc)
A_inv.sort(key=lambda row: row[-1])
A_inv = np.delete(A_inv, -1, 1)
print(formatting(comm.rank, format_action('merge results')))
t_inv.finish()
write_matrix(A_inv, out)
x = np.dot(A_inv, b)
print(
formatting(comm.rank, format_action('product A_inv on b',
x=x.tolist())))
out.write(('{}\n' + '{:.3f}\t' * len(x)).format(1, *x))
t.finish()
else:
t = Timer('proc{}'.format(comm.rank))
n = comm.bcast(None, root=master)
step = n / comm.size
if not step:
diff_proc_max = dm
diff_max_global = comm.reduce(diff_proc_max, op=MPI.MAX, root=MASTER)
diff_max_global = comm.bcast(diff_max_global, root=MASTER)
iter += 1
if comm.rank == MASTER:
print(f'[END] iterations: {iter}')
with open('output.txt', 'w') as file:
for i in range(n // comm.size + 1):
for j in range(N):
file.write(f'{u[i, j]} ')
vec = np.zeros(N)
for k in range(1, comm.size):
size = (n // comm.size + 2) if k == LAST else (n // comm.size +
1)
for i in range(1, size):
vec = comm.recv(source=k)
for val in vec:
file.write(f'{val} ')
totalTimer.finish()
else:
for i in range((n // comm.size +
2) if comm.rank == LAST else (n // comm.size + 1)):
comm.send(u[i], dest=MASTER)
