1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
""" Class for handling several simultaneous jobs.
The class has been tested on Niflheim-opteron4.
"""
from multiprocessing import Pool
import time
from ase.io import write, read
class MultiprocessingRun:
"""Class that allows for the simultaneous relaxation of
several candidates on a cluster. Best used if each individual
calculation is too small for using a queueing system.
Parameters:
data_connection: DataConnection object.
tmp_folder: Folder for temporary files.
n_simul: The number of simultaneous relaxations.
relax_function: The relaxation function. This needs to return
the filename of the relaxed structure.
"""
def __init__(self, data_connection, relax_function,
tmp_folder, n_simul=None):
self.dc = data_connection
self.pool = Pool(n_simul)
self.relax_function = relax_function
self.tmp_folder = tmp_folder
self.results = []
def relax(self, a):
"""Relax the atoms object a by submitting the relaxation
to the pool of cpus."""
self.dc.mark_as_queued(a)
fname = '{0}/cand{1}.traj'.format(self.tmp_folder,
a.info['confid'])
write(fname, a)
self.results.append(self.pool.apply_async(self.relax_function,
[fname]))
self._cleanup()
def _cleanup(self):
for r in self.results:
if r.ready() and r.successful():
fname = r.get()
a = read(fname)
self.dc.add_relaxed_step(a)
self.results.remove(r)
def finish_all(self):
"""Checks that all calculations are finished, if not
wait and check again. Return when all are finished."""
while len(self.results) > 0:
self._cleanup()
time.sleep(2.)
|
