vocab = Vocabulary()
vocab.read_from_precomputed(name_dir_out)
size_window = 2
d = collections.deque(maxlen=size_window)
for i in range(size_window):
d.append(-1)
#matrix=dok_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
#matrix=lil_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
#matrix=dok_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
cnt_workers = 2
m = ArrayOfTrees(vocab.cnt_words)
def get_start_i(N, cnt_workers, id_worker):
if N < cnt_workers:
return min(N, id_worker)
length_of_range = ((N + 1) // cnt_workers)
start = length_of_range * id_worker
if id_worker < N % cnt_workers:
start += id_worker
else:
start += N % cnt_workers
return start
def get_interval(N, cnt_workers, id_worker):
# process_file(os.path.join(root,items))
lst_files=rndrobin_list(lst_files,cnt_mappers,id_worker)
#print("I'm mapper {}, processing files in ".format(id_mapper),lst_files)
for f in lst_files:
process_file(f)
#send unfinished buffers
for id_dest in range(cnt_reducers):
for pos_buf in range(pos_bufers[id_dest],size_buffer):
buffers[id_dest][pos_buf][0]=-1
comm.Send(buffers[id_dest], dest=id_dest+cnt_mappers, tag=1)
print ("m{} finished! sppend {:.2f} s on waiting Send".format(id_worker,timings["wait_send"]))
#print (lst_files)
else: #this is reducer
timings["collecting"]-=timer()
rstart,rend=get_interval(cnt_words,cnt_reducers,id_reducer)
m=ArrayOfTrees(rend-rstart)
print ("I'm reducer {} of {} running on {}, my ownership range is from {} to {}".format(id_reducer,cnt_reducers,MPI.Get_processor_name(),rstart,rend))
buffer = np.empty((size_buffer,2), dtype=np.int64)
cnt_mappers_finished=0
has_work=True
while has_work:
#print("r{}: waiting rcv".format(id_reducer))
sys.stdout.flush()
comm.Recv(buffer, source=MPI.ANY_SOURCE, tag=1)
#print ("r{} recvd {}".format(id_reducer,buffer.shape))
for i in range(size_buffer):
if buffer[i,0]>=0:
m.accumulate(int(buffer[i][0]-rstart),int(buffer[i][1]))#todo mapping for aot
else:
cnt_mappers_finished+=1
#print("r{}: one mapper finished".format(id_reducer))
lst_files = rndrobin_list(lst_files, cnt_mappers, id_worker)
#print("I'm mapper {}, processing files in ".format(id_mapper),lst_files)
for f in lst_files:
process_file(f)
#send unfinished buffers
for id_dest in range(cnt_reducers):
for pos_buf in range(pos_bufers[id_dest], size_buffer):
buffers[id_dest][pos_buf][0] = -1
comm.Send(buffers[id_dest], dest=id_dest + cnt_mappers, tag=1)
print("m{} finished! sppend {:.2f} s on waiting Send".format(
id_worker, timings["wait_send"]))
#print (lst_files)
else: #this is reducer
timings["collecting"] -= timer()
rstart, rend = get_interval(cnt_words, cnt_reducers, id_reducer)
m = ArrayOfTrees(rend - rstart)
print(
"I'm reducer {} of {} running on {}, my ownership range is from {} to {}"
.format(id_reducer, cnt_reducers, MPI.Get_processor_name(), rstart,
rend))
buffer = np.empty((size_buffer, 2), dtype=np.int64)
cnt_mappers_finished = 0
has_work = True
while has_work:
#print("r{}: waiting rcv".format(id_reducer))
sys.stdout.flush()
comm.Recv(buffer, source=MPI.ANY_SOURCE, tag=1)
#print ("r{} recvd {}".format(id_reducer,buffer.shape))
for i in range(size_buffer):
if buffer[i, 0] >= 0:
m.accumulate(int(buffer[i][0] - rstart),
vocab=Vocabulary()
vocab.read_from_precomputed(name_dir_out)
size_window=2
d = collections.deque(maxlen=size_window)
for i in range(size_window):
d.append(-1)
#matrix=dok_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
#matrix=lil_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
#matrix=dok_matrix((vocab.cnt_words, vocab.cnt_words), dtype=np.int64)
cnt_workers=2
m=ArrayOfTrees(vocab.cnt_words)
def get_start_i(N,cnt_workers,id_worker):
if N<cnt_workers: return min(N,id_worker)
length_of_range=((N+1)//cnt_workers)
start = length_of_range*id_worker
if id_worker<N%cnt_workers:
start+=id_worker
else:
start+=N%cnt_workers
return start
def get_interval(N,cnt_workers,id_worker):
return (get_start_i(N,cnt_workers,id_worker),get_start_i(N,cnt_workers,id_worker+1))
def get_worker_id(N,cnt_workers,v):
