def server_proc():
async def server(w):
with w.comm.ctx.socket(zmq.REP) as new_task_socket:
new_task_socket.bind(bind_addr)
while not w.stop:
if new_task_socket.poll(timeout=0) == 0:
await asyncio.sleep(0)
task_bytes = new_task_socket.recv()
task = cloudpickle.loads(task_bytes)
out = await w.wait_for_work(task)
out_bytes = cloudpickle.dumps(out)
new_task_socket.send(out_bytes)
tsk.cluster(2, server)
def run_tsk_parallel():
n_cores = 2
async def submit(w):
# A = np.random.rand(job_size, job_size)
# r = w.memory.put(A)
# def fnc(w):
# A_inside = tsk.remote_get(r)
# return invert(w, A_inside)
fnc_dref = w.memory.put(
serialized=taskloaf.serialize.dumps(lambda w: long_fnc(0)))
async with tsk.profile.Profiler(w, range(n_cores)):
start = time.time()
out = await wait_all(
[tsk.task(w, fnc_dref, to=i % n_cores) for i in range(n_jobs)])
print('inside: ', time.time() - start)
return tsk.cluster(n_cores, submit)
import taskloaf as tsk
from taskloaf.promise import task, when_all
async def submit(w):
X = 3.1
n = 10
pr = task(w, lambda w: task(w, lambda w: X))
for i in range(n):
pr = pr.then(lambda w, x: x + 1)
pr = when_all([pr, task(w, lambda w: X, to=1)]).then(lambda w, x: sum(x))
print('answer is', await pr)
if __name__ == "__main__":
tsk.cluster(2, submit)
import taskloaf as tsk
async def submit(w):
n = await tsk.task(w, lambda w: 10, to = 1)
pr = tsk.when_all(
[tsk.task(w, lambda w, i = i: i, to = i % 2) for i in range(n)]
).then(lambda w, x: sum(x))
return (await pr)
if __name__ == "__main__":
result = tsk.cluster(2, submit)
print(result)
assert(result == 45)
inner_chunk_size = int(1e9)
t.report(str(w.addr) + ' setup')
for i in range(0, indptr.shape[0], inner_chunk_size):
_sparse.csrmv(indptr[i:(i + inner_chunk_size + 1)], indices, data,
v, out[i:(i + inner_chunk_size)], False)
await asyncio.sleep(0)
t.report(str(w.addr) + ' dot')
# return out_dref
dot_dref = put_fnc(w, dot)
# await run_dot()
async with tsk.Profiler(w, range(0)):
t.report('put/startprof')
for i in range(4):
print('')
print('')
print('')
await map(w,
dot_dref,
len(matrix_chunks),
time.time(),
n_super_chunks=n_super_chunks)
t.report('dot')
# tsk.cluster(n_cores, submit)
tsk.cluster(n_cores, submit2)
import taskloaf as tsk
async def submit(w):
await tsk.task(w, lambda w: print('hI'))
if __name__ == "__main__":
tsk.run(submit)
tsk.cluster(1, submit)
tsk.cluster(1, submit, runner=tsk.mpirun)
async def submit(w):
async def submit2(w):
print("HI!")
tsk.cluster(2, submit2)
for pr in setup_prs:
await pr
import time
start = time.time()
n_tasks = 8 * 2
for j in range(10):
prs = []
for i in range(n_tasks):
prs.append(tsk.task(gpu_run, to=i % n_workers))
for i in range(n_tasks):
await prs[i]
print(time.time() - start)
n_workers = 8
tsk.cluster(n_workers, submit)
#
# async def work_builder():
# print("YO!")
# addr = tsk.get_service('comm').addr
# def add_task():
# print("PEACE" + str(addr))
# return addr
# rem_addr = await tsk.task(add_task, to = gpu_addr)
# return (2.0, rem_addr)
#
# def f2(x):
# return x * 2
# pr1 = tsk.task(work_builder, to = 0).then(f2)