def grafoCompleto(size):
if size <= 0:
raise ValueError("o tamanho do grafo deve ser um número positivo")
g = Grafo()
g.add_vertice("0")
for i in range(1, size):
for j in g.vertices:
g.add_aresta(str(i), str(j))
return g
def main():
g1 = Grafo(False) # gera um grafo sem direção
v1 = Vertice("a", 12) # cria o vérice v1
g1.add_vertice(v1) # insere o vérice v1 no grafo g1
v2 = Vertice("b", 13) # cria o vértice v2
g1.add_vertice(v2) # insere o vértice v2 no grafo g1
v3 = Vertice("c", 6) # cria o vértice v3
g1.add_vertice(v3) # insere o cértice v3 no grafo v3
a1 = Aresta(v1, v2, "a1", 2) # cria uma aresta entre v1 e v2
a2 = Aresta(v2, v3, "a2", 2) # cria uma aresta entre v2 e v3
a3 = Aresta(v3, v1, "a3", 2) # cria uma aresta entre v3 e v1
# corrigir
g1.add_aresta(a1) # insere a aresta a1 no grafo
g1.add_aresta(a2) # insere a aresta a2 no grafo
g1.add_aresta(a3) # insere a aresta a3 no grafo
print(g1)
g1.getFTD(v1)
g1.dfs()
def grafoNaoCordal(size):
g = Grafo()
if (size < 4):
raise ValueError("Qualquer grafo com menos de 4 vértices é cordal")
# criando ciclo de tamanho 4 (subgrafo proibido para tornar o grafo não cordal)
for i in range(0, 4):
if (i == 3):
g.add_aresta(str(i), str(0))
else:
g.add_aresta(str(i), str(i + 1))
# Inserindo novos vértices considerando o tamanho definido pelo usuário
for i in range(4, size):
for j in g.vertices:
g.add_aresta(str(i), str(j))
return g
def colocation_pairs_optimal(queue, degradation_limit):
try:
import sys
import pickle
#Depois colocar esse "/opt/slurm/lib/degradation_model/" pra
#ser pego da variável de ambiente
sys.path.insert(0, '/opt/slurm/lib/degradation_model/graph/')
#Arquivo apenas necessário para propósitos de debug
#with open('/tmp/PYTHON_PATH.txt', 'a') as f:
# print >> f, 'Filename:', sys.path # Python 2.x
#Importing graph structure
from grafo import Grafo
from blossom_min import *
grafo = Grafo()
schedule = []
apps_counters = {}
joblist = []
#creating dictionary for building degradation graph
for job in queue:
jobid = job[0]
apps_counters[jobid] = job[1]
joblist.append(jobid)
#Load machine learning model
#loaded_model = pickle.load(open("linear_regression.sav", 'rb'))
loaded_model = pickle.load(
open("/opt/slurm/lib/degradation_model/mlpregressor.sav", 'rb'))
#Load scaling used on training fase
scaling_model = pickle.load(
open("/opt/slurm/lib/degradation_model/scaling.sav", 'rb'))
#For each job create degradation graph
for jobMain in joblist:
for jobSecond in joblist:
if (jobMain != jobSecond):
prediction = apps_counters[jobMain] + apps_counters[
jobSecond]
prediction_normalized = scaling_model.transform(
[prediction])
degradationMain = loaded_model.predict(
prediction_normalized)
prediction = apps_counters[jobSecond] + apps_counters[
jobMain]
prediction_normalized = scaling_model.transform(
[prediction])
degradationSecond = loaded_model.predict(
prediction_normalized)
#print("[{r1} {r2}]{r3} {r4}".format(r1=jobMain, r2=jobSecond, r3=degradationMain, r4=degradationSecond))
#grafo.add_aresta(str(jobMain), str(jobSecond), max(degradationMain, degradationSecond))
grafo.add_aresta(
jobMain, jobSecond,
max(degradationMain[0], degradationSecond[0]))
#Apply minimum weight perfect matching to find optimal co-schedule
blossom = min_weight_matching(grafo)
#Creating Output
schedule_s = []
joblist_pairs = blossom.keys()
with open('/tmp/SLURM_PYTHON_SCHEDULE_DEBUG.txt', 'a') as f:
print >> f, 'EXECUTION:' # Python 2.x
print >> f, 'PAIRS CREATED: ', blossom # Python 2.x
for key in joblist_pairs:
jobid1 = key
jobid2 = blossom[key][0]
degradation = blossom[key][1]
if (degradation > degradation_limit):
schedule.append([jobid1])
schedule.append([jobid2])
else:
schedule.append(sorted((jobid1, jobid2)))
schedule_s = sorted(schedule, key=lambda tup: tup[0])
print >> f, 'FINAL RESULT: ', schedule_s # Python 2.x
f.closed
return schedule_s
except Exception, e:
with open('/tmp/SLURM_PYTHON_ERROR.txt', 'a') as f:
print >> f, 'Filename:', type(e) # Python 2.x
print >> f, 'Filename:', str(e) # Python 2.x
print >> f, 'queue:', queue # Python 2.x
print >> f, 'Filename:', type(queue) # Python 2.x
for job in queue:
print >> f, 'type job[0]', type(job[0])
print >> f, 'type job[1]', type(job[1])
print >> f, '++++++++++++++++++++++++:' # Python 2.x
print >> f, 'degradation_limit:', degradation_limit # Python 2.x
print >> f, 'Filename:', type(degradation_limit) # Python 2.x
#print('Filename:', str(e), file=f) # Python 3.x
f.closed