Commit 6633cd95 authored by Iker Martín Álvarez's avatar Iker Martín Álvarez
Browse files

RMA functionality and refactor of many of the codes

parent 2f81e29c
import sys
import glob
import numpy as np
import pandas as pd
from enum import Enum
class G_enum(Enum):
TOTAL_RESIZES = 0
TOTAL_GROUPS = 1
TOTAL_STAGES = 2
GRANULARITY = 3
SDR = 4
ADR = 5
DR = 6
RED_METHOD = 7
RED_STRATEGY = 8
SPAWN_METHOD = 9
SPAWN_STRATEGY = 10
GROUPS = 11
FACTOR_S = 12
DIST = 13
STAGE_TYPES = 14
STAGE_TIMES = 15
STAGE_BYTES = 16
ITERS = 17
ASYNCH_ITERS = 18
T_ITER = 19
T_STAGES = 20
T_SPAWN = 21
T_SPAWN_REAL = 22
T_SR = 23
T_AR = 24
T_MALLEABILITY = 25
T_TOTAL = 26
#Malleability specific
NP = 0
NC = 1
#Iteration specific
IS_DYNAMIC = 11
N_PARENTS = 17
#columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
# "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Groups", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
# "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_Malleability", "T_total"] #27
columnsL = ["NP", "NC", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
"Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Is_Dynamic", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
"Stage_Bytes", "N_Parents", "Asynch_Iters", "T_iter", "T_stages"] #20
def copy_iteration(row, dataL_it, group, iteration, is_asynch):
basic_indexes = [G_enum.TOTAL_STAGES.value, G_enum.GRANULARITY.value, \
G_enum.STAGE_TYPES.value, G_enum.STAGE_TIMES.value, G_enum.STAGE_BYTES.value]
basic_asynch = [G_enum.SDR.value, G_enum.ADR.value, G_enum.DR.value]
array_asynch_group = [G_enum.RED_METHOD.value, G_enum.RED_STRATEGY.value, \
G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value, G_enum.DIST.value]
dataL_it[G_enum.FACTOR_S.value] = row[G_enum.FACTOR_S.value][group]
dataL_it[G_enum.NP.value] = row[G_enum.GROUPS.value][group]
dataL_it[G_enum.ASYNCH_ITERS.value] = is_asynch
dataL_it[G_enum.T_ITER.value] = row[G_enum.T_ITER.value][group][iteration]
dataL_it[G_enum.T_STAGES.value] = list(row[G_enum.T_STAGES.value][group][iteration])
dataL_it[G_enum.IS_DYNAMIC.value] = True if group > 0 else False
for index in basic_indexes:
dataL_it[index] = row[index]
for index in array_asynch_group:
dataL_it[index] = [None, -1]
dataL_it[index][0] = row[index][group]
dataL_it[G_enum.N_PARENTS.value] = -1
if group > 0:
dataL_it[G_enum.N_PARENTS.value] = row[G_enum.GROUPS.value][group-1]
if is_asynch:
dataL_it[G_enum.NC.value] = row[G_enum.GROUPS.value][group+1]
for index in basic_asynch:
dataL_it[index] = row[index]
for index in array_asynch_group:
dataL_it[index][1] = row[index][group+1]
for index in array_asynch_group: # Convert to tuple
dataL_it[index] = tuple(dataL_it[index])
#-----------------------------------------------
def write_iter_dataframe(dataL, name, i, first=False):
dfL = pd.DataFrame(dataL, columns=columnsL)
dfL.to_pickle(name + str(i) + '.pkl')
if first:
print(dfL)
#-----------------------------------------------
def create_iter_dataframe(dfG, name, max_it_L):
it = -1
file_i = 0
first = True
dataL = []
for row_index in range(len(dfG)):
row = dfG.iloc[row_index]
groups = row[G_enum.TOTAL_GROUPS.value]
for group in range(groups):
real_iterations = len(row[G_enum.T_ITER.value][group])
real_asynch = row[G_enum.ASYNCH_ITERS.value][group]
is_asynch = False
for iteration in range(real_iterations-real_asynch):
it += 1
dataL.append( [None] * len(columnsL) )
copy_iteration(row, dataL[it], group, iteration, is_asynch)
is_asynch = True
for iteration in range(real_iterations-real_asynch, real_iterations):
it += 1
dataL.append( [None] * len(columnsL) )
copy_iteration(row, dataL[it], group, iteration, is_asynch)
if it >= max_it_L-1: #Var "it" starts at -1, so one more must be extracted for precise cut
write_iter_dataframe(dataL, name, file_i, first)
dataL = []
file_i += 1
first = False
it = -1
if it != -1:
write_iter_dataframe(dataL, name, file_i)
#-----------------------------------------------
if len(sys.argv) < 2:
print("The files name is missing\nUsage: python3 CreateIterDataframe.py input_file.pkl output_name [max_rows_per_file]")
exit(1)
input_name = sys.argv[1]
if len(sys.argv) > 2:
name = sys.argv[2]
else:
name = "dataL"
print("File names will be: " + name + ".pkl")
if len(sys.argv) > 3:
max_it_L = int(sys.argv[3])
else:
max_it_L = 100000
dfG = pd.read_pickle(input_name)
print(dfG)
create_iter_dataframe(dfG, name, max_it_L)
import sys
import glob
import numpy as np
import pandas as pd
from enum import Enum
class G_enum(Enum):
TOTAL_RESIZES = 0
TOTAL_GROUPS = 1
TOTAL_STAGES = 2
GRANULARITY = 3
SDR = 4
ADR = 5
DR = 6
RED_METHOD = 7
RED_STRATEGY = 8
SPAWN_METHOD = 9
SPAWN_STRATEGY = 10
GROUPS = 11
FACTOR_S = 12
DIST = 13
STAGE_TYPES = 14
STAGE_TIMES = 15
STAGE_BYTES = 16
ITERS = 17
ASYNCH_ITERS = 18
T_ITER = 19
T_STAGES = 20
T_SPAWN = 21
T_SPAWN_REAL = 22
T_SR = 23
T_AR = 24
T_MALLEABILITY = 25
T_TOTAL = 26
#Malleability specific
NP = 0
NC = 1
#Iteration specific
IS_DYNAMIC = 11
N_PARENTS = 17
#columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
# "Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Groups", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
# "Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_Malleability", "T_total"] #27
columnsM = ["NP", "NC", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
"Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "FactorS", "Dist", "Stage_Type", "Stage_Time", \
"Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_Malleability"] #25
def copy_resize(row, dataM_it, resize):
basic_indexes = [G_enum.TOTAL_STAGES.value, G_enum.GRANULARITY.value, G_enum.SDR.value, \
G_enum.ADR.value, G_enum.DR.value]
basic_group = [G_enum.STAGE_TYPES.value, G_enum.STAGE_TIMES.value, G_enum.STAGE_BYTES.value]
array_actual_group = [G_enum.FACTOR_S.value, G_enum.ITERS.value, G_enum.ASYNCH_ITERS.value, \
G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, \
G_enum.T_AR.value, G_enum.T_MALLEABILITY.value, G_enum.T_ITER.value, G_enum.T_STAGES.value]
array_next_group = [G_enum.RED_METHOD.value, G_enum.RED_STRATEGY.value, \
G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value]
dataM_it[G_enum.NP.value] = row[G_enum.GROUPS.value][resize]
dataM_it[G_enum.NC.value] = row[G_enum.GROUPS.value][resize+1]
dataM_it[G_enum.DIST.value-1] = [None, None]
dataM_it[G_enum.DIST.value-1][0] = row[G_enum.DIST.value][resize]
dataM_it[G_enum.DIST.value-1][1] = row[G_enum.DIST.value][resize+1]
for index in basic_indexes:
dataM_it[index] = row[index]
for index in basic_group:
dataM_it[index-1] = row[index]
for index in array_actual_group:
dataM_it[index-1] = row[index][resize]
for index in array_next_group:
dataM_it[index] = row[index][resize+1]
#-----------------------------------------------
def create_resize_dataframe(dfG, dataM):
it = -1
for row_index in range(len(dfG)):
row = dfG.iloc[row_index]
resizes = row[G_enum.TOTAL_RESIZES.value]
for resize in range(resizes):
it += 1
dataM.append( [None] * len(columnsM) )
copy_resize(row, dataM[it], resize)
#-----------------------------------------------
if len(sys.argv) < 2:
print("The files name is missing\nUsage: python3 CreateResizeDataframe.py input_file.pkl output_name")
exit(1)
input_name = sys.argv[1]
if len(sys.argv) > 2:
name = sys.argv[2]
else:
name = "dataM"
print("File name will be: " + name + ".pkl")
dfG = pd.read_pickle(input_name)
dataM = []
create_resize_dataframe(dfG, dataM)
dfM = pd.DataFrame(dataM, columns=columnsM)
dfM.to_pickle(name + '.pkl')
print(dfG)
print(dfM)
......@@ -12,34 +12,56 @@ class G_enum(Enum):
SDR = 4
ADR = 5
DR = 6
ASYNCH_REDISTRIBUTION_TYPE = 7
SPAWN_METHOD = 8
SPAWN_STRATEGY = 9
GROUPS = 10
FACTOR_S = 11
DIST = 12
STAGE_TYPES = 13
STAGE_TIMES = 14
STAGE_BYTES = 15
ITERS = 16
ASYNCH_ITERS = 17
T_ITER = 18
T_STAGES = 19
T_SPAWN = 20
T_SPAWN_REAL = 21
T_SR = 22
T_AR = 23
T_TOTAL = 24
columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Asynch_Redistribution_Type", \
"Spawn_Method", "Spawn_Strategy", "Groups", "Factor_S", "Dist", "Stage_Types", "Stage_Times", "Stage_Bytes", \
"Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_total"] #25
RED_METHOD = 7
RED_STRATEGY = 8
SPAWN_METHOD = 9
SPAWN_STRATEGY = 10
GROUPS = 11
FACTOR_S = 12
DIST = 13
STAGE_TYPES = 14
STAGE_TIMES = 15
STAGE_BYTES = 16
ITERS = 17
ASYNCH_ITERS = 18
T_ITER = 19
T_STAGES = 20
T_SPAWN = 21
T_SPAWN_REAL = 22
T_SR = 23
T_AR = 24
T_MALLEABILITY = 25
T_TOTAL = 26
#Malleability specific
NP = 0
NC = 1
#Iteration specific
IS_DYNAMIC = 11
N_PARENTS = 17
columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Redistribution_Method", \
"Redistribution_Strategy", "Spawn_Method", "Spawn_Strategy", "Groups", "FactorS", "Dist", "Stage_Types", "Stage_Times", \
"Stage_Bytes", "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_Malleability", "T_total"] #27
#-----------------------------------------------
# Obtains the value of a given index in a splited line
# and returns it as a float values
def get_value(line, index):
return float(line[index].split('=')[1].split(',')[0])
# and returns it as a float values if possible, string otherwise
def get_value(line, index, separator=True):
if separator:
value = line[index].split('=')[1].split(',')[0]
else:
value = line[index]
try:
value = float(value)
if value.is_integer():
value = int(value)
except ValueError:
return value
return value
#-----------------------------------------------
# Obtains the general parameters of an execution and
# stores them for creating a global dataframe
def record_config_line(lineS, dataG_it):
......@@ -48,27 +70,25 @@ def record_config_line(lineS, dataG_it):
offset_line = 2
for i in range(len(ordered_indexes)):
value = get_value(lineS, i+offset_line)
if value.is_integer():
value = int(value)
index = ordered_indexes[i]
dataG_it[index] = value
dataG_it[G_enum.TOTAL_GROUPS.value] = dataG_it[G_enum.TOTAL_RESIZES.value]
dataG_it[G_enum.TOTAL_RESIZES.value] -=1 #FIXME Modificar en App sintetica
dataG_it[G_enum.TOTAL_GROUPS.value] = dataG_it[G_enum.TOTAL_RESIZES.value]+1
#FIXME Modificar cuando ADR ya no sea un porcentaje
dataG_it[G_enum.DR.value] = dataG_it[G_enum.SDR.value] + dataG_it[G_enum.ADR.value]
# Init lists for each column
array_groups = [G_enum.GROUPS.value, G_enum.FACTOR_S.value, G_enum.DIST.value, G_enum.ITERS.value, \
G_enum.ASYNCH_ITERS.value, G_enum.T_ITER.value, G_enum.T_STAGES.value]
array_resizes = [G_enum.ASYNCH_REDISTRIBUTION_TYPE.value, G_enum.SPAWN_METHOD.value, \
G_enum.SPAWN_STRATEGY.value, G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, \
G_enum.T_SR.value, G_enum.T_AR.value]
G_enum.ASYNCH_ITERS.value, G_enum.T_ITER.value, G_enum.T_STAGES.value, G_enum.RED_METHOD.value, \
G_enum.RED_STRATEGY.value, G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value,]
array_resizes = [ G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, G_enum.T_AR.value, G_enum.T_MALLEABILITY.value]
array_stages = [G_enum.STAGE_TYPES.value, \
G_enum.STAGE_TIMES.value, G_enum.STAGE_BYTES.value]
for index in array_groups:
dataG_it[index] = [None]*dataG_it[G_enum.TOTAL_GROUPS.value]
for group in range(dataG_it[G_enum.TOTAL_GROUPS.value]):
dataG_it[G_enum.T_ITER.value][group] = []
for index in array_resizes:
dataG_it[index] = [None]*dataG_it[G_enum.TOTAL_RESIZES.value]
......@@ -76,6 +96,7 @@ def record_config_line(lineS, dataG_it):
for index in array_stages:
dataG_it[index] = [None]*dataG_it[G_enum.TOTAL_STAGES.value]
#-----------------------------------------------
# Obtains the parameters of a stage line
# and stores it in the dataframe
# Is needed to indicate in which stage is
......@@ -86,144 +107,194 @@ def record_stage_line(lineS, dataG_it, stage):
offset_lines = 2
for i in range(len(array_stages)):
value = get_value(lineS, i+offset_lines)
if value.is_integer():
value = int(value)
index = array_stage[i]
index = array_stages[i]
dataG_it[index][stage] = value
#-----------------------------------------------
# Obtains the parameters of a resize line
# and stores them in the dataframe
# Is needed to indicate to which group refers
# the resize line
def record_resize_line(lineS, dataG_it, group):
array_stages = [G_enum.ITERS.value, G_enum.GROUPS.value, G_enum.FACTOR_S.value, G_enum.DIST.value, \
G_enum.ASYNCH_REDISTRIBUTION_TYPE.value, G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value]
def record_group_line(lineS, dataG_it, group):
array_groups = [G_enum.ITERS.value, G_enum.GROUPS.value, G_enum.FACTOR_S.value, G_enum.DIST.value, \
G_enum.RED_METHOD.value, G_enum.RED_STRATEGY.value, G_enum.SPAWN_METHOD.value, G_enum.SPAWN_STRATEGY.value]
offset_lines = 2
for i in range(len(array_stages)):
for i in range(len(array_groups)):
value = get_value(lineS, i+offset_lines)
if value.is_integer():
value = int(value)
index = array_stage[i]
index = array_groups[i]
dataG_it[index][group] = value
#-----------------------------------------------
def record_time_line(lineS, dataG_it):
T_names = ["T_spawn:", "T_spawn_real:", "T_SR:", "T_AR:", "T_total:"]
T_values = [G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, G_enum.T_AR.value, G_enum.T_TOTAL.value]
T_names = ["T_spawn:", "T_spawn_real:", "T_SR:", "T_AR:", "T_Malleability:", "T_total:"]
T_values = [G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, G_enum.T_AR.value, G_enum.T_MALLEABILITY.value, G_enum.T_TOTAL.value]
if not (lineS[0] in T_names): # Execute only if line represents a Time
return
index = T_names.index(linesS[0])
index = T_names.index(lineS[0])
index = T_values[index]
offset_lines = 1
for i in range(len(dataG_it[index])):
value = get_value(lineS, i+offset_lines)
dataG_it[index][i] = value
len_index = 1
if dataG_it[index] != None:
len_index = len(dataG_it[index])
for i in range(len_index):
dataG_it[index][i] = get_value(lineS, i+offset_lines, False)
else:
dataG_it[index] = get_value(lineS, offset_lines, False)
#-----------------------------------------------
def read_global_file(f, dataG, it):
resizes = 0
timer = 0
previousNP = 0
def record_multiple_times_line(lineS, dataG_it, group):
T_names = ["T_iter:", "T_stage"]
T_values = [G_enum.T_ITER.value, G_enum.T_STAGES.value]
if not (lineS[0] in T_names): # Execute only if line represents a Time
return
index = T_names.index(lineS[0])
index = T_values[index]
offset_lines = 1
if index == G_enum.T_STAGES.value:
offset_lines += 1
total_iters = len(lineS)-offset_lines
stage = int(lineS[1].split(":")[0])
if stage == 0:
dataG_it[index][group] = [None] * total_iters
for i in range(total_iters):
dataG_it[index][group][i] = [None] * dataG_it[G_enum.TOTAL_STAGES.value]
for i in range(total_iters):
dataG_it[index][group][i][stage] = get_value(lineS, i+offset_lines, False)
else:
total_iters = len(lineS)-offset_lines
for i in range(total_iters):
dataG_it[index][group].append(get_value(lineS, i+offset_lines, False))
#-----------------------------------------------
def read_local_file(f, dataG, it, runs_in_file):
offset = 0
real_it = 0
group = 0
for line in f:
lineS = line.split()
if len(lineS) > 0:
if lineS[0] == "Config": # CONFIG LINE
it += 1
dataG.append([None]*(25+1))
#dataG[it][-1] = None Indicates if local data has been recorded(1) or not(None)
record_config(lineS, dataG[it])
resize = 0
stage = 0
elif lineS[0] == "Stage":
record_stage_line(lineS, dataG[it], stage)
stage+=1
elif lineS[0] == "Resize":
record_resize_line(lineS, dataG[it], resize)
resize+=1
elif lineS[0] == "T_total:":
value = get_value(lineS, 1)
dataG[it][G_enum.T_TOTAL.value] = value
if lineS[0] == "Group": # GROUP number
offset += 1
real_it = it - (runs_in_file-offset)
group = int(lineS[1].split(":")[0])
elif lineS[0] == "Async_Iters:":
offset_line = 1
dataG[real_it][G_enum.ASYNCH_ITERS.value][group] = get_value(lineS, offset_line, False)
else:
record_time_line(lineS, dataG[it])
return it
record_multiple_times_line(lineS, dataG[real_it], group)
#-----------------------------------------------
def read_local_file(f, dataG, it):
resizes = 0
timer = 0
previousNP = 0
def read_global_file(f, dataG, it):
runs_in_file=0
for line in f:
lineS = line.split()
if len(lineS) > 0:
if lineS[0] == "Config": # CONFIG LINE
it += 1
record_config(lineS, dataG[it], dataM[it])
resize = 0
runs_in_file += 1
group = 0
stage = 0
dataG.append([None]*len(columnsG))
record_config_line(lineS, dataG[it])
elif lineS[0] == "Stage":
record_stage_line(lineS, dataG[it], stage)
stage+=1
elif lineS[0] == "Resize":
record_resize_line(lineS, dataG[it], resize)
resize+=1
elif lineS[0] == "T_total:":
value = get_value(lineS, 1)
dataG[it][G_enum.T_TOTAL.value] = value
elif lineS[0] == "Group":
record_group_line(lineS, dataG[it], group)
group+=1
else:
record_time_line(lineS, dataG[it])
return it
return it,runs_in_file
#-----------------------------------------------
#columnsG = ["Total_Resizes", "Total_Groups", "Total_Stages", "Granularity", "SDR", "ADR", "DR", "Asynch_Redistribution_Type", \\
# "Spawn_Method", "Spawn_Strategy", "Groups", "Dist", "Stage_Types", "Stage_Times", "Stage_Bytes", \\
# "Iters", "Asynch_Iters", "T_iter", "T_stages", "T_spawn", "T_spawn_real", "T_SR", "T_AR", "T_total"] #24
#-----------------------------------------------
def convert_to_tuples(dfG):
array_list_items = [G_enum.GROUPS.value, G_enum.FACTOR_S.value, G_enum.DIST.value, G_enum.ITERS.value, \
G_enum.ASYNCH_ITERS.value, G_enum.RED_METHOD.value, G_enum.RED_STRATEGY.value, G_enum.SPAWN_METHOD.value, \
G_enum.SPAWN_STRATEGY.value, G_enum.T_SPAWN.value, G_enum.T_SPAWN_REAL.value, G_enum.T_SR.value, \
G_enum.T_AR.value, G_enum.STAGE_TYPES.value, G_enum.STAGE_TIMES.value, G_enum.STAGE_BYTES.value]
#TODO Falta T_malleability?
array_multiple_list_items = [G_enum.T_ITER.value, G_enum.T_STAGES.value]
for item in array_list_items:
name = columnsG[item]
values = dfG[name].copy()
for index in range(len(values)):
values[index] = tuple(values[index])
dfG[name] = values
for item in array_multiple_list_items:
name = columnsG[item]
values = dfG[name].copy()
for i in range(len(values)):
for j in range(len(values[i])):
if(type(values[i][j][0]) == list):
for r in range(len(values[i][j])):
values[i][j][r] = tuple(values[i][j][r])
values[i][j] = tuple(values[i][j])
values[i] = tuple(values[i])
dfG[name] = values
#-----------------------------------------------
if len(sys.argv) < 2:
print("The files name is missing\nUsage: python3 iterTimes.py resultsName directory csvOutName")
print("The files name is missing\nUsage: python3 MallTimes.py commonName directory OutName")
exit(1)
common_name = sys.argv[1]
if len(sys.argv) >= 3:
BaseDir = sys.argv[2]
print("Searching in directory: "+ BaseDir)
else:
BaseDir = sys.argv[2]
BaseDir = "./"
if len(sys.argv) >= 4:
print("Csv name will be: " + sys.argv[3] + "G.csv & " + sys.argv[3] + "M.csv")
name = sys.argv[3]
else:
name = "data"
print("File name will be: " + name + "G.pkl")
insideDir = "Run"
lista = glob.glob("./" + BaseDir + insideDir + "*/" + sys.argv[1]+ "*Global.o*")
lista += (glob.glob("./" + BaseDir + sys.argv[1]+ "*Global.o*")) # Se utiliza cuando solo hay un nivel de directorios
lista = glob.glob(BaseDir + insideDir + "*/" + common_name + "*_Global.out")
lista += (glob.glob(BaseDir + common_name + "*_Global.out")) # Se utiliza cuando solo hay un nivel de directorios
print("Number of files found: "+ str(len(lista)));
it = -1
dataG = []
dataM = []
columnsG = ["N", "%Async", "Groups", "NP", "NS", "Dist", "Matrix", "CommTam", "Cst", "Css", "Time", "Iters", "TE"] #13
columnsM = ["N", "%Async", "NP", "NS", "Dist", "Matrix", "CommTam", "Cst", "Css", "Time", "Iters", "TC", "TH", "TS", "TA"] #15
for elem in lista:
f = open(elem, "r")
it = read_file(f, dataG, dataM, it)
id_run = elem.split("_Global.out")[0].split(common_name)[1]
path_to_run = elem.split(common_name)[0]
lista_local = glob.glob(path_to_run + common_name + id_run + "_G*NP*.out")
it,runs_in_file = read_global_file(f, dataG, it)
f.close()
for elem_local in lista_local:
f_local = open(elem_local, "r")
read_local_file(f_local, dataG, it, runs_in_file)
f_local.close()
#print(data)
dfG = pd.DataFrame(dataG, columns=columnsG)
dfG.to_csv(name + 'G.csv')
convert_to_tuples(dfG)
print(dfG)
dfG.to_pickle(name + 'G.pkl')
dfM = pd.DataFrame(dataM, columns=columnsM)
#dfM = pd.DataFrame(dataM, columns=columnsM)
#Poner en TC el valor real y en TH el necesario para la app
cond = dfM.TH != 0
dfM.loc[cond, ['TC', 'TH']] = dfB.loc[cond, ['TH', 'TC']].values
dfM.to_csv(name + 'M.csv')
#cond = dfM.TH != 0
#dfM.loc[cond, ['TC', 'TH']] = dfM.loc[cond, ['TH', 'TC']].values
#dfM.to_csv(name + 'M.csv')
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'''
Created on Oct 24, 2016
@author: David Llorens (dllorens@uji.es)
(c) Universitat Jaume I 2016
@license: GPL2
'''
from abc import ABCMeta, abstractmethod
infinity = float("infinity")
## Esquema para BT básico --------------------------------------------------------------------------
class PartialSolution(metaclass=ABCMeta):
@abstractmethod
def is_solution(self)-> "bool":
pass
@abstractmethod
def get_solution(self) -> "solution":
pass
@abstractmethod
def successors(self) -> "IEnumerable<PartialSolution>":
pass
class BacktrackingSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolution") -> "IEnumerable<Solution>":
def bt(ps):
if ps.is_solution():
yield ps.get_solution()
else:
for new_ps in ps.successors():
yield from bt(new_ps)
yield from bt(initial_ps)
class BacktrackingSolverOld(metaclass=ABCMeta):
def solve(self, initial_ps : "PartialSolution") -> "IEnumerable<Solution>":
def bt(ps):
if ps.is_solution():
return [ps.get_solution()]
else:
solutions = []
for new_ps in ps.successors():
solutions.extend(bt(new_ps))
return solutions
return bt(initial_ps)
## Esquema para BT con control de visitados --------------------------------------------------------
class PartialSolutionWithVisitedControl(PartialSolution):
@abstractmethod
def state(self)-> "state":
# the returned object must be of an inmutable type
pass
class BacktrackingVCSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolutionWithVisitedControl") -> "IEnumerable<Solution>":
def bt(ps):
seen.add(ps.state())
if ps.is_solution():
yield ps.get_solution()
else:
for new_ps in ps.successors():
state = new_ps.state()
if state not in seen:
yield from bt(new_ps)
seen = set()
yield from bt(initial_ps)
## Esquema para BT para optimización ----------------------------------------------------------------
class PartialSolutionWithOptimization(PartialSolutionWithVisitedControl):
@abstractmethod
def f(self)-> "int or double":
# result of applying the objective function to the partial solution
pass
class BacktrackingOptSolver(metaclass=ABCMeta):
@staticmethod
def solve(initial_ps : "PartialSolutionWithOptimization") -> "IEnumerable<Solution>":
def bt(ps):
nonlocal best_solution_found_score
ps_score = ps.f()
best_seen[ps.state()] = ps_score
if ps.is_solution() and ps_score < best_solution_found_score: #sólo muestra una solución si mejora la última mostrada
best_solution_found_score = ps_score
yield ps.get_solution()
else:
for new_ps in ps.successors():
state = new_ps.state()
if state not in best_seen or new_ps.f() < best_seen[state]:
yield from bt(new_ps)
best_seen = {}
best_solution_found_score = infinity
yield from bt(initial_ps)
import sys
import glob
import numpy as numpy
import pandas as pd
#-----------------------------------------------
def read_file(f, dataA, dataB, itA, itB):
compute_tam = 0
comm_tam = 0
sdr = 0
adr = 0
dist = 0
css = 0
cst = 0
time = 0
recording = False
it_line = 0
aux_itA = 0
aux_itB = 0
iters = 0
np = 0
np_par = 0
ns = 0
array = []
columnas = ['Titer','Ttype','Top']
#print(f)
for line in f:
lineS = line.split()
if len(lineS) > 1:
if recording and lineS[0].split(':')[0] in columnas: #Record data
aux_itA = 0
lineS.pop(0)
if it_line==0:
for observation in lineS:
dataA.append([None]*15)
dataA[itA+aux_itA][0] = sdr
dataA[itA+aux_itA][1] = adr
dataA[itA+aux_itA][2] = np
dataA[itA+aux_itA][3] = np_par
dataA[itA+aux_itA][4] = ns
dataA[itA+aux_itA][5] = dist
dataA[itA+aux_itA][6] = compute_tam
dataA[itA+aux_itA][7] = comm_tam
dataA[itA+aux_itA][8] = cst
dataA[itA+aux_itA][9] = css
dataA[itA+aux_itA][10] = time
dataA[itA+aux_itA][11] = iters
dataA[itA+aux_itA][12] = float(observation)
array.append(float(observation))
aux_itA+=1
elif it_line==1:
deleted = 0
for observation in lineS:
dataA[itA+aux_itA][13] = float(observation)
if float(observation) == 0:
array.pop(aux_itA - deleted)
deleted+=1
aux_itA+=1
else:
for observation in lineS:
dataA[itA+aux_itA][14] = float(observation)
aux_itA+=1
it_line += 1
if(it_line % 3 == 0): # Comprobar si se ha terminado de mirar esta ejecucion
recording = False
it_line = 0
itA = itA + aux_itA
if ns != 0: # Solo obtener datos de grupos con hijos
dataB.append([None]*14)
dataB[itB][0] = sdr
dataB[itB][1] = adr
dataB[itB][2] = np
dataB[itB][3] = np_par
dataB[itB][4] = ns
dataB[itB][5] = dist
dataB[itB][6] = compute_tam
dataB[itB][7] = comm_tam
dataB[itB][8] = cst
dataB[itB][9] = css
dataB[itB][10] = time
dataB[itB][11] = iters
dataB[itB][12] = tuple(array)
dataB[itB][13] = numpy.sum(array)
itB+=1
array = []
if lineS[0] == "Config:":
compute_tam = int(lineS[1].split('=')[1].split(',')[0])
comm_tam = int(lineS[2].split('=')[1].split(',')[0])
sdr = int(lineS[3].split('=')[1].split(',')[0])
adr = int(lineS[4].split('=')[1].split(',')[0])
css = int(lineS[6].split('=')[1].split(',')[0])
cst = int(lineS[7].split('=')[1].split(',')[0])
time = float(lineS[8].split('=')[1])
elif lineS[0] == "Config":
recording = True
iters = int(lineS[2].split('=')[1].split(',')[0])
dist = int(lineS[4].split('=')[1].split(',')[0])
np = int(lineS[5].split('=')[1].split(',')[0])
np_par = int(lineS[6].split('=')[1].split(',')[0])
ns = int(float(lineS[7].split('=')[1]))
return itA,itB
#-----------------------------------------------
#Config: matrix=1000, sdr=1000000000, adr=0, aib=0 time=2.000000
#Config Group: iters=100, factor=1.000000, phy=2, procs=2, parents=0, sons=4
#Ttype: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
if len(sys.argv) < 2:
print("The files name is missing\nUsage: python3 iterTimes.py resultsName directory csvOutName")
exit(1)
if len(sys.argv) >= 3:
BaseDir = sys.argv[2]
print("Searching in directory: "+ BaseDir)
else: #FIXME
BaseDir = sys.argv[2]
if len(sys.argv) >= 4:
print("Csv name will be: " + sys.argv[3] + ".csv and "+ sys.argv[3] + "_Total.csv")
name = sys.argv[3]
else:
name = "data"
insideDir = "Run"
lista = glob.glob("./" + BaseDir + insideDir + "*/" + sys.argv[1]+ "*ID*.o*")
print("Number of files found: "+ str(len(lista)));
itA = itB = 0
dataA = []
dataB = [] #0 #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14
columnsA = ["N", "%Async", "NP", "N_par", "NS", "Dist", "Compute_tam", "Comm_tam", "Cst", "Css","Time", "Iters", "Ti", "Tt", "To"] #15
columnsB = ["N", "%Async", "NP", "N_par", "NS", "Dist", "Compute_tam", "Comm_tam", "Cst", "Css","Time", "Iters", "Ti", "Sum"] #14
for elem in lista:
f = open(elem, "r")
itA,itB = read_file(f, dataA, dataB, itA, itB)
f.close()
#print(data)
dfA = pd.DataFrame(dataA, columns=columnsA)
dfB = pd.DataFrame(dataB, columns=columnsB)
dfA['N'] += dfA['%Async']
dfA['%Async'] = (dfA['%Async'] / dfA['N']) * 100
dfA.to_csv(name + '.csv')
dfB['N'] += dfB['%Async']
dfB['%Async'] = (dfB['%Async'] / dfB['N']) * 100
dfB.to_csv(name + '_Total.csv')
......@@ -3,22 +3,19 @@ import glob
import numpy as numpy
import pandas as pd
if len(sys.argv) < 3:
print("The files name is missing\nUsage: python3 joinDf.py resultsName1.csv resultsName2.csv csvOutName")
print("The files name is missing\nUsage: python3 joinDf.py resultsName1.pkl resultsName2.pkl OutName")
exit(1)
if len(sys.argv) >= 4:
print("Csv name will be: " + sys.argv[3] + ".csv")
name = sys.argv[3]
else:
name = "dataJOINED"
df1 = pd.read_csv( sys.argv[1] )
df2 = pd.read_csv( sys.argv[2] )
print("File name will be: " + name + ".pkl")
df1 = pd.read_pickle( sys.argv[1] )
df2 = pd.read_pickle( sys.argv[2] )
frames = [df1, df2]
df3 = pd.concat(frames)
df3 = df3.drop(columns=df3.columns[0])
df3.to_csv(name + '.csv')
df3.to_pickle(name + '.pkl')
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......@@ -42,9 +42,9 @@ static int handler(void* user, const char* section, const char* name,
} else if (MATCH("general", "Granularity")) {
pconfig->granularity = atoi(value);
} else if (MATCH("general", "SDR")) { // TODO Refactor a nombre manual
pconfig->sdr = atoi(value);
pconfig->sdr = strtoul(value, NULL, 10);
} else if (MATCH("general", "ADR")) { // TODO Refactor a nombre manual
pconfig->adr = atoi(value);
pconfig->adr = strtoul(value, NULL, 10);
} else if (MATCH("general", "Rigid")) {
pconfig->rigid_times = atoi(value);
......@@ -72,8 +72,10 @@ static int handler(void* user, const char* section, const char* name,
aux_value = MALL_DIST_SPREAD;
}
pconfig->groups[pconfig->actual_group].phy_dist = aux_value;
} else if (MATCH(resize_name, "Asynch_Redistribution_Type") && LAST(pconfig->actual_group, pconfig->n_groups)) {
pconfig->groups[pconfig->actual_group].at = atoi(value);
} else if (MATCH(resize_name, "Redistribution_Method") && LAST(pconfig->actual_group, pconfig->n_groups)) {
pconfig->groups[pconfig->actual_group].rm = atoi(value);
} else if (MATCH(resize_name, "Redistribution_Strategy") && LAST(pconfig->actual_group, pconfig->n_groups)) {
pconfig->groups[pconfig->actual_group].rs = atoi(value);
} else if (MATCH(resize_name, "Spawn_Method") && LAST(pconfig->actual_group, pconfig->n_groups)) {
pconfig->groups[pconfig->actual_group].sm = atoi(value);
} else if (MATCH(resize_name, "Spawn_Strategy") && LAST(pconfig->actual_group, pconfig->n_groups)) {
......
......@@ -41,14 +41,14 @@ void comm_results(results_data *results, int root, size_t resizes, MPI_Comm inte
* En concreto son tres escalares y dos vectores de tamaño "resizes"
*/
void def_results_type(results_data *results, int resizes, MPI_Datatype *results_type) {
int i, counts = 6;
int blocklengths[] = {1, 1, 1, 1, 1, 1};
int i, counts = 7;
int blocklengths[] = {1, 1, 1, 1, 1, 1, 1};
MPI_Aint displs[counts], dir;
MPI_Datatype types[counts];
// Rellenar vector types
types[0] = types[1] = types[2] = types[3] = types[4] = types[5] = MPI_DOUBLE;
blocklengths[2] = blocklengths[3] = blocklengths[4] = blocklengths[5] = resizes;
types[0] = types[1] = types[2] = types[3] = types[4] = types[5] = types[6] = MPI_DOUBLE;
blocklengths[2] = blocklengths[3] = blocklengths[4] = blocklengths[5] = blocklengths[6] = resizes;
// Rellenar vector displs
MPI_Get_address(results, &dir);
......@@ -59,6 +59,7 @@ void def_results_type(results_data *results, int resizes, MPI_Datatype *results_
MPI_Get_address(results->async_time, &displs[3]);
MPI_Get_address(results->spawn_real_time, &displs[4]);
MPI_Get_address(results->spawn_time, &displs[5]);
MPI_Get_address(results->malleability_time, &displs[6]);
for(i=0;i<counts;i++) displs[i] -= dir;
......@@ -87,6 +88,7 @@ void set_results_post_reconfig(results_data *results, int grp, int sdr, int adr)
} else {
results->async_time[grp-1] = 0;
}
results->malleability_time[grp-1] = results->malleability_end - results->malleability_time[grp-1];
}
/*
......@@ -100,6 +102,7 @@ void set_results_post_reconfig(results_data *results, int grp, int sdr, int adr)
*/
void reset_results_index(results_data *results) {
results->iter_index = 0;
results->iters_async = 0;
}
//=============================================================== FIXME BORRAR?
......@@ -162,17 +165,18 @@ void compute_results_stages(results_data *results, int myId, int numP, int root,
int i;
if(myId == root) {
for(i=0; i<stages; i++) {
MPI_Reduce(MPI_IN_PLACE, results->stage_times[i], results->iter_index, MPI_DOUBLE, MPI_SUM, root, comm);
for(size_t j=0; j<results->iter_index; j++) {
MPI_Reduce(MPI_IN_PLACE, results->stage_times[i], results->iter_index, MPI_DOUBLE, MPI_MAX, root, comm);
/* for(size_t j=0; j<results->iter_index; j++) {
results->stage_times[i][j] = results->stage_times[i][j] / numP;
}
}*/
}
}
else {
for(i=0; i<stages; i++) {
MPI_Reduce(results->stage_times[i], NULL, results->iter_index, MPI_DOUBLE, MPI_SUM, root, comm);
MPI_Reduce(results->stage_times[i], NULL, results->iter_index, MPI_DOUBLE, MPI_MAX, root, comm);
}
}
//MPI_Barrier(comm); //FIXME Esto debería de borrarse
}
//======================================================||
......@@ -189,12 +193,12 @@ void compute_results_stages(results_data *results, int myId, int numP, int root,
void print_iter_results(results_data results) {
size_t i;
printf("Async_Iters: %ld\n", results.iters_async);
printf("T_iter: ");
for(i=0; i< results.iter_index; i++) {
printf("%lf ", results.iters_time[i]);
}
printf("\nAsync_Iters: %ld\n", results.iters_async);
printf("\n");
}
/*
......@@ -240,6 +244,11 @@ void print_global_results(results_data results, size_t resizes) {
printf("%lf ", results.async_time[i]);
}
printf("\nT_Malleability: ");
for(i=0; i < resizes; i++) {
printf("%lf ", results.malleability_time[i]);
}
printf("\nT_total: %lf\n", results.exec_time);
}
......@@ -262,6 +271,7 @@ void init_results_data(results_data *results, size_t resizes, size_t stages, siz
results->spawn_real_time = calloc(resizes, sizeof(double));
results->sync_time = calloc(resizes, sizeof(double));
results->async_time = calloc(resizes, sizeof(double));
results->malleability_time = calloc(resizes, sizeof(double));
results->wasted_time = 0;
results->iters_size = iters_size + RESULTS_EXTRA_SIZE;
......@@ -280,20 +290,24 @@ void realloc_results_iters(results_data *results, size_t stages, size_t needed)
int error = 0;
double *time_aux;
size_t i;
if(results->iters_size >= needed) return;
time_aux = (double *) realloc(results->iters_time, needed * sizeof(double));
if(time_aux == NULL) error = 1;
for(i=0; i<stages; i++) { //TODO Comprobar que no da error el realloc
results->stage_times[i] = (double *) realloc(results->stage_times[i], needed * sizeof(double));
if(results->stage_times[i] == NULL) error = 1;
}
if(time_aux == NULL) error = 1;
if(error) {
fprintf(stderr, "Fatal error - No se ha podido realojar la memoria de resultados\n");
MPI_Abort(MPI_COMM_WORLD, 1);
}
results->iters_time = time_aux;
results->iters_size = needed;
}
/*
......@@ -318,6 +332,10 @@ void free_results_data(results_data *results, size_t stages) {
free(results->async_time);
results->async_time = NULL;
}
if(results->malleability_time != NULL) {
free(results->malleability_time);
results->malleability_time = NULL;
}
if(results->iters_time != NULL) {
free(results->iters_time);
......
......@@ -14,8 +14,9 @@ typedef struct {
// Spawn, Thread, Sync, Async and Exec time
double spawn_start, *spawn_time, *spawn_real_time;
double sync_start, sync_end, *sync_time;
double async_start, async_end, *async_time;
double sync_end, *sync_time;
double async_end, *async_time;
double malleability_end, *malleability_time;
double exec_start, exec_time;
double wasted_time; // Time spent recalculating iter stages
} results_data;
......
......@@ -12,6 +12,8 @@
#include "../malleability/malleabilityManager.h"
#include "../malleability/malleabilityStates.h"
#define DR_MAX_SIZE 1000000000
int work();
double iterate(int async_comm);
double iterate_relaxed(double *time, double *times_stages);
......@@ -37,6 +39,7 @@ int main(int argc, char *argv[]) {
int numP, myId, res;
int req;
int im_child;
size_t i;
int num_cpus, num_nodes;
char *nodelist = NULL;
......@@ -54,6 +57,8 @@ int main(int argc, char *argv[]) {
if(req != MPI_THREAD_MULTIPLE) {
printf("No se ha obtenido la configuración de hilos necesaria\nSolicitada %d -- Devuelta %d\n", req, MPI_THREAD_MULTIPLE);
fflush(stdout);
MPI_Abort(MPI_COMM_WORLD, -50);
}
init_group_struct(argv, argc, myId, numP);
......@@ -66,11 +71,27 @@ int main(int argc, char *argv[]) {
set_benchmark_configuration(config_file);
set_benchmark_results(results);
if(config_file->n_groups > 1) {
set_malleability_configuration(config_file->groups[group->grp+1].sm, config_file->groups[group->grp+1].ss,
config_file->groups[group->grp+1].phy_dist, config_file->groups[group->grp+1].rm, config_file->groups[group->grp+1].rs);
set_children_number(config_file->groups[group->grp+1].procs); // TODO TO BE DEPRECATED
malleability_add_data(&(group->grp), 1, MAL_INT, 1, 1);
malleability_add_data(&run_id, 1, MAL_INT, 1, 1);
malleability_add_data(&(group->iter_start), 1, MAL_INT, 1, 1);
if(config_file->sdr) {
for(i=0; i<group->sync_data_groups; i++) {
malleability_add_data(group->sync_array[i], group->sync_qty[i], MAL_CHAR, 0, 1);
}
}
if(config_file->adr) {
for(i=0; i<group->async_data_groups; i++) {
malleability_add_data(group->async_array[i], group->async_qty[i], MAL_CHAR, 0, 0);
}
}
}
MPI_Barrier(comm);
results->exec_start = MPI_Wtime();
} else { //Init hijos
......@@ -82,6 +103,7 @@ int main(int argc, char *argv[]) {
// TODO Refactor - Que sea una unica funcion
// Obtiene las variables que van a utilizar los hijos
void *value = NULL;
size_t entries;
malleability_get_data(&value, 0, 1, 1);
group->grp = *((int *)value);
......@@ -91,7 +113,25 @@ int main(int argc, char *argv[]) {
malleability_get_data(&value, 2, 1, 1);
group->iter_start = *((int *)value);
if(config_file->sdr) {
malleability_get_entries(&entries, 0, 1);
group->sync_array = (char **) malloc(entries * sizeof(char *));
for(i=0; i<entries; i++) {
malleability_get_data(&value, i, 0, 1);
group->sync_array[i] = (char *)value;
}
}
if(config_file->adr) {
malleability_get_entries(&entries, 0, 0);
group->async_array = (char **) malloc(entries * sizeof(char *));
for(i=0; i<entries; i++) {
malleability_get_data(&value, i, 0, 0);
group->async_array[i] = (char *)value;
}
}
group->grp = group->grp + 1;
realloc_results_iters(results, config_file->n_stages, config_file->groups[group->grp].iters);
}
//
......@@ -105,14 +145,15 @@ int main(int argc, char *argv[]) {
MPI_Comm_rank(comm, &(group->myId));
group->grp = group->grp + 1;
set_benchmark_grp(group->grp);
if(group->grp != 0) {
obtain_op_times(1); //Obtener los nuevos valores de tiempo para el computo
obtain_op_times(0); //Obtener los nuevos valores de tiempo para el computo
set_results_post_reconfig(results, group->grp, config_file->sdr, config_file->adr);
}
if(config_file->n_groups != group->grp + 1) { //TODO Llevar a otra funcion
set_malleability_configuration(config_file->groups[group->grp+1].sm, config_file->groups[group->grp+1].ss,
config_file->groups[group->grp+1].phy_dist, config_file->groups[group->grp+1].at, -1);
config_file->groups[group->grp+1].phy_dist, config_file->groups[group->grp+1].rm, config_file->groups[group->grp+1].rs);
set_children_number(config_file->groups[group->grp+1].procs); // TODO TO BE DEPRECATED
if(group->grp != 0) {
......@@ -122,11 +163,11 @@ int main(int argc, char *argv[]) {
res = work();
if(res == MALL_ZOMBIE) break;
if(res==1) { // Se ha llegado al final de la aplicacion
MPI_Barrier(comm); // TODO Posible error al utilizar SHRINK
MPI_Barrier(comm);
results->exec_time = MPI_Wtime() - results->exec_start - results->wasted_time;
}
print_local_results();
reset_results_index(results);
} while(config_file->n_groups > group->grp + 1 && config_file->groups[group->grp+1].sm == MALL_SPAWN_MERGE);
......@@ -180,8 +221,8 @@ int work() {
state = malleability_checkpoint();
iter = 0;
while(state == MALL_DIST_PENDING || state == MALL_SPAWN_PENDING || state == MALL_SPAWN_SINGLE_PENDING || state == MALL_SPAWN_ADAPT_POSTPONE) {
if(iter < config_file->groups[group->grp+1].iters) {
while(state == MALL_DIST_PENDING || state == MALL_SPAWN_PENDING || state == MALL_SPAWN_SINGLE_PENDING || state == MALL_SPAWN_ADAPT_POSTPONE || state == MALL_SPAWN_ADAPT_PENDING) {
if(group->grp+1 < config_file->n_groups && iter < config_file->groups[group->grp+1].iters) {
iterate(state);
iter++;
group->iter_start = iter;
......@@ -227,6 +268,7 @@ double iterate(int async_comm) {
results->iters_async += 1;
}
// TODO Pasar el resto de este código a results.c
if(results->iter_index == results->iters_size) { // Aumentar tamaño de ambos vectores de resultados
realloc_results_iters(results, config_file->n_stages, results->iters_size + 100);
}
......@@ -235,6 +277,7 @@ double iterate(int async_comm) {
results->stage_times[i][results->iter_index] = times_stages_aux[i];
}
results->iter_index = results->iter_index + 1;
// TODO Pasar hasta aqui
free(times_stages_aux);
......@@ -395,6 +438,8 @@ void init_group_struct(char *argv[], int argc, int myId, int numP) {
* se comunican con los padres para inicializar sus datos.
*/
void init_application() {
int i, last_index;
if(group->argc < 2) {
printf("Falta el fichero de configuracion. Uso:\n./programa config.ini id\nEl argumento numerico id es opcional\n");
MPI_Abort(MPI_COMM_WORLD, -1);
......@@ -407,10 +452,29 @@ void init_application() {
results = malloc(sizeof(results_data));
init_results_data(results, config_file->n_resizes, config_file->n_stages, config_file->groups[group->grp].iters);
if(config_file->sdr) {
malloc_comm_array(&(group->sync_array), config_file->sdr , group->myId, group->numP);
group->sync_data_groups = config_file->sdr % DR_MAX_SIZE ? config_file->sdr/DR_MAX_SIZE+1 : config_file->sdr/DR_MAX_SIZE;
group->sync_qty = (int *) malloc(group->sync_data_groups * sizeof(int));
group->sync_array = (char **) malloc(group->sync_data_groups * sizeof(char *));
last_index = group->sync_data_groups-1;
for(i=0; i<last_index; i++) {
group->sync_qty[i] = DR_MAX_SIZE;
malloc_comm_array(&(group->sync_array[i]), group->sync_qty[i], group->myId, group->numP);
}
group->sync_qty[last_index] = config_file->sdr % DR_MAX_SIZE ? config_file->sdr % DR_MAX_SIZE : DR_MAX_SIZE;
malloc_comm_array(&(group->sync_array[last_index]), group->sync_qty[last_index], group->myId, group->numP);
}
if(config_file->adr) {
malloc_comm_array(&(group->async_array), config_file->adr , group->myId, group->numP);
group->async_data_groups = config_file->adr % DR_MAX_SIZE ? config_file->adr/DR_MAX_SIZE+1 : config_file->adr/DR_MAX_SIZE;
group->async_qty = (int *) malloc(group->async_data_groups * sizeof(int));
group->async_array = (char **) malloc(group->async_data_groups * sizeof(char *));
last_index = group->async_data_groups-1;
for(i=0; i<last_index; i++) {
group->async_qty[i] = DR_MAX_SIZE;
malloc_comm_array(&(group->async_array[i]), group->async_qty[i], group->myId, group->numP);
}
group->async_qty[last_index] = config_file->adr % DR_MAX_SIZE ? config_file->adr % DR_MAX_SIZE : DR_MAX_SIZE;
malloc_comm_array(&(group->async_array[last_index]), group->async_qty[last_index], group->myId, group->numP);
}
obtain_op_times(1);
......@@ -440,13 +504,29 @@ void obtain_op_times(int compute) {
* Libera toda la memoria asociada con la aplicacion
*/
void free_application_data() {
if(config_file->sdr) {
size_t i;
if(config_file->sdr && group->sync_array != NULL) {
for(i=0; i<group->sync_data_groups; i++) {
free(group->sync_array[i]);
group->sync_array[i] = NULL;
}
free(group->sync_qty);
group->sync_qty = NULL;
free(group->sync_array);
group->sync_array = NULL;
}
if(config_file->adr) {
if(config_file->adr && group->async_array != NULL) {
for(i=0; i<group->async_data_groups; i++) {
free(group->async_array[i]);
group->async_array[i] = NULL;
}
free(group->async_qty);
group->async_qty = NULL;
free(group->async_array);
group->async_array = NULL;
}
free_malleability();
free_results_data(results, config_file->n_stages);
......
......@@ -15,13 +15,14 @@ typedef struct {
unsigned int grp;
int iter_start;
int argc;
size_t sync_data_groups, async_data_groups;
int numS; // Cantidad de procesos hijos
MPI_Comm children, parents;
char *compute_comm_array, *compute_comm_recv;
char **argv;
char *sync_array, *async_array;
char **sync_array, **async_array;
int *sync_qty, *async_qty;
} group_data;
......@@ -48,7 +49,7 @@ typedef struct
typedef struct
{
int iters, procs;
int sm, ss, phy_dist, at;
int sm, ss, phy_dist, rm, rs;
float factor;
} group_config_t;
......@@ -57,7 +58,8 @@ typedef struct
size_t n_groups, n_resizes, n_stages; // n_groups==n_resizes+1
size_t actual_group, actual_stage;
int rigid_times;
int granularity, sdr, adr;
int granularity;
size_t sdr, adr;
MPI_Datatype config_type, group_type, iter_stage_type;
iter_stage_t *stages;
......
......@@ -71,7 +71,8 @@ void malloc_config_resizes(configuration *user_config) {
user_config->groups[i].sm = 0;
user_config->groups[i].ss = 1;
user_config->groups[i].phy_dist = 0;
user_config->groups[i].at = 0;
user_config->groups[i].rm = 0;
user_config->groups[i].rs = 1;
user_config->groups[i].factor = 1;
}
def_struct_groups(user_config);
......@@ -135,18 +136,14 @@ void free_config(configuration *user_config) {
}
}
//Liberar tipos derivados
if(user_config->config_type != MPI_DATATYPE_NULL) {
MPI_Type_free(&(user_config->config_type));
user_config->config_type = MPI_DATATYPE_NULL;
}
if(user_config->group_type != MPI_DATATYPE_NULL) {
MPI_Type_free(&(user_config->group_type));
user_config->group_type = MPI_DATATYPE_NULL;
}
if(user_config->iter_stage_type != MPI_DATATYPE_NULL) {
MPI_Type_free(&(user_config->iter_stage_type));
user_config->iter_stage_type = MPI_DATATYPE_NULL;
}
free(user_config->groups);
free(user_config->stages);
......@@ -162,17 +159,17 @@ void free_config(configuration *user_config) {
void print_config(configuration *user_config) {
if(user_config != NULL) {
size_t i;
printf("Config loaded: R=%zu, S=%zu, granularity=%d, SDR=%d, ADR=%d\n",
printf("Config loaded: R=%zu, S=%zu, granularity=%d, SDR=%zu, ADR=%zu\n",
user_config->n_resizes, user_config->n_stages, user_config->granularity, user_config->sdr, user_config->adr);
for(i=0; i<user_config->n_stages; i++) {
printf("Stage %zu: PT=%d, T_stage=%lf, bytes=%d, T_capped=%d\n",
i, user_config->stages[i].pt, user_config->stages[i].t_stage, user_config->stages[i].real_bytes, user_config->stages[i].t_capped);
}
for(i=0; i<user_config->n_groups; i++) {
printf("Group %zu: Iters=%d, Procs=%d, Factors=%f, Dist=%d, AT=%d, SM=%d, SS=%d\n",
printf("Group %zu: Iters=%d, Procs=%d, Factors=%f, Dist=%d, RM=%d, RS=%d, SM=%d, SS=%d\n",
i, user_config->groups[i].iters, user_config->groups[i].procs, user_config->groups[i].factor,
user_config->groups[i].phy_dist, user_config->groups[i].at, user_config->groups[i].sm,
user_config->groups[i].ss);
user_config->groups[i].phy_dist, user_config->groups[i].rm, user_config->groups[i].rs,
user_config->groups[i].sm, user_config->groups[i].ss);
}
}
}
......@@ -194,16 +191,16 @@ void print_config_group(configuration *user_config, size_t grp) {
sons = user_config->groups[grp+1].procs;
}
printf("Config: granularity=%d, SDR=%d, ADR=%d\n",
printf("Config: granularity=%d, SDR=%zu, ADR=%zu\n",
user_config->granularity, user_config->sdr, user_config->adr);
for(i=0; i<user_config->n_stages; i++) {
printf("Stage %zu: PT=%d, T_stage=%lf, bytes=%d, T_capped=%d\n",
i, user_config->stages[i].pt, user_config->stages[i].t_stage, user_config->stages[i].real_bytes, user_config->stages[i].t_capped);
}
printf("Group %zu: Iters=%d, Procs=%d, Factors=%f, Dist=%d, AT=%d, SM=%d, SS=%d, parents=%d, children=%d\n",
printf("Group %zu: Iters=%d, Procs=%d, Factors=%f, Dist=%d, RM=%d, RS=%d, SM=%d, SS=%d, parents=%d, children=%d\n",
grp, user_config->groups[grp].iters, user_config->groups[grp].procs, user_config->groups[grp].factor,
user_config->groups[grp].phy_dist, user_config->groups[grp].at, user_config->groups[grp].sm,
user_config->groups[grp].ss, parents, sons);
user_config->groups[grp].phy_dist, user_config->groups[grp].rm, user_config->groups[grp].rs,
user_config->groups[grp].sm, user_config->groups[grp].ss, parents, sons);
}
}
......@@ -270,17 +267,17 @@ void def_struct_config_file(configuration *config_file) {
MPI_Datatype types[counts];
// Rellenar vector types
types[0] = types[1] = MPI_UNSIGNED_LONG;
types[2] = types[3] = types[4] = types[5] = MPI_INT;
types[0] = types[1] = types[2] = types[3] = MPI_UNSIGNED_LONG;
types[4] = types[5] = MPI_INT;
// Rellenar vector displs
MPI_Get_address(config_file, &dir);
MPI_Get_address(&(config_file->n_groups), &displs[0]);
MPI_Get_address(&(config_file->n_stages), &displs[1]);
MPI_Get_address(&(config_file->granularity), &displs[2]);
MPI_Get_address(&(config_file->sdr), &displs[3]);
MPI_Get_address(&(config_file->adr), &displs[4]);
MPI_Get_address(&(config_file->sdr), &displs[2]);
MPI_Get_address(&(config_file->adr), &displs[3]);
MPI_Get_address(&(config_file->granularity), &displs[4]);
MPI_Get_address(&(config_file->rigid_times), &displs[5]);
for(i=0;i<counts;i++) displs[i] -= dir;
......@@ -295,15 +292,15 @@ void def_struct_config_file(configuration *config_file) {
* en una sola comunicacion.
*/
void def_struct_groups(configuration *config_file) {
int i, counts = 7;
int blocklengths[7] = {1, 1, 1, 1, 1, 1, 1};
int i, counts = 8;
int blocklengths[8] = {1, 1, 1, 1, 1, 1, 1, 1};
MPI_Aint displs[counts], dir;
MPI_Datatype aux, types[counts];
group_config_t *groups = config_file->groups;
// Rellenar vector types
types[0] = types[1] = types[2] = types[3] = types[4] = types[5] = MPI_INT;
types[6] = MPI_FLOAT;
types[0] = types[1] = types[2] = types[3] = types[4] = types[5] = types[6] = MPI_INT;
types[7] = MPI_FLOAT;
// Rellenar vector displs
MPI_Get_address(groups, &dir);
......@@ -313,8 +310,9 @@ void def_struct_groups(configuration *config_file) {
MPI_Get_address(&(groups->sm), &displs[2]);
MPI_Get_address(&(groups->ss), &displs[3]);
MPI_Get_address(&(groups->phy_dist), &displs[4]);
MPI_Get_address(&(groups->at), &displs[5]);
MPI_Get_address(&(groups->factor), &displs[6]);
MPI_Get_address(&(groups->rm), &displs[5]);
MPI_Get_address(&(groups->rs), &displs[6]);
MPI_Get_address(&(groups->factor), &displs[7]);
for(i=0;i<counts;i++) displs[i] -= dir;
......@@ -326,7 +324,7 @@ void def_struct_groups(configuration *config_file) {
// Tipo derivado para enviar N elementos de la estructura
MPI_Type_create_resized(aux, 0, sizeof(group_config_t), &(config_file->group_type));
MPI_Type_commit(&(config_file->group_type));
// MPI_Type_free(&aux); //FIXME It should be freed
MPI_Type_free(&aux);
}
}
......@@ -364,6 +362,6 @@ void def_struct_iter_stage(configuration *config_file) {
// Tipo derivado para enviar N elementos de la estructura
MPI_Type_create_resized(aux, 0, sizeof(iter_stage_t), &(config_file->iter_stage_type));
MPI_Type_commit(&(config_file->iter_stage_type));
// MPI_Type_free(&aux); //FIXME It should be freed
MPI_Type_free(&aux);
}
}
CC = gcc
MCC = mpicc
#C_FLAGS_ALL = -Wconversion -Wpedantic
C_FLAGS = -Wall -Wextra -Wshadow -Wfatal-errors -g
C_FLAGS = -Wall -Wextra -Wshadow -Wfatal-errors
LD_FLAGS = -lm -pthread
DEF =
......
This diff is collapsed.
......@@ -16,13 +16,18 @@
//#define MAL_USE_POINT 2
//#define MAL_USE_THREAD 3
int send_sync(char *array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_child);
void recv_sync(char **array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_parents);
int sync_communication(char *send, char **recv, int qty, int myId, int numP, int numO, int is_children_group, int comm_type, MPI_Comm comm);
//int async_communication(char *send, char **recv, int qty, int myId, int numP, int numO, int is_children_group, int red_method, int red_strategies, MPI_Comm comm, MPI_Request **requests, size_t *request_qty);
int send_async(char *array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_child, MPI_Request **comm_req, int parents_wait);
void recv_async(char **array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_parents, int parents_wait);
int async_communication_start(char *send, char **recv, int qty, int myId, int numP, int numO, int is_children_group, int red_method, int red_strategies, MPI_Comm comm, MPI_Request **requests, size_t *request_qty, MPI_Win *win);
int async_communication_check(int myId, int is_children_group, int red_strategies, MPI_Comm comm, MPI_Request *requests, size_t request_qty);
void async_communication_wait(int red_strategies, MPI_Comm comm, MPI_Request *requests, size_t request_qty);
void async_communication_end(int red_method, int red_strategies, MPI_Request *requests, size_t request_qty, MPI_Win *win);
//int send_async(char *array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_child, MPI_Request **comm_req, int red_method, int red_strategies);
//void recv_async(char **array, int qty, int myId, int numP, MPI_Comm intercomm, int numP_parents, int red_method, int red_strategies);
void malloc_comm_array(char **array, int qty, int myId, int numP);
int malleability_red_contains_strat(int comm_strategies, int strategy, int *result);
int malleability_red_add_strat(int *comm_strategies, int strategy);
#endif
......@@ -3,7 +3,7 @@
#include <mpi.h>
#include "block_distribution.h"
void set_interblock_counts(int id, int numP, struct Dist_data data_dist, int *sendcounts);
void set_interblock_counts(int id, int numP, struct Dist_data data_dist, int offset_ids, int *sendcounts);
void get_util_ids(struct Dist_data dist_data, int numP_other, int **idS);
/*
......@@ -13,22 +13,43 @@ void get_util_ids(struct Dist_data dist_data, int numP_other, int **idS);
*
* The struct should be freed with freeCounts
*/
void prepare_comm_alltoall(int myId, int numP, int numP_other, int n, struct Counts *counts) {
int i, *idS;
struct Dist_data dist_data;
void prepare_comm_alltoall(int myId, int numP, int numP_other, int n, int offset_ids, struct Counts *counts) {
int i, *idS, first_id = 0;
struct Dist_data dist_data, dist_target;
if(counts == NULL) {
fprintf(stderr, "Counts is NULL for rank %d/%d ", myId, numP);
MPI_Abort(MPI_COMM_WORLD, -3);
}
get_block_dist(n, myId, numP, &dist_data);
mallocCounts(counts, numP_other);
get_util_ids(dist_data, numP_other, &idS);
if(idS[0] == 0) {
set_interblock_counts(0, numP_other, dist_data, counts->counts);
idS[0]++;
counts->idI = idS[0] + offset_ids;
counts->idE = idS[1] + offset_ids;
get_block_dist(n, idS[0], numP_other, &dist_target); // RMA Specific operation -- uses idS[0], not idI
counts->first_target_displs = dist_data.ini - dist_target.ini; // RMA Specific operation
if(idS[0] == 0) { // Uses idS[0], not idI
set_interblock_counts(counts->idI, numP_other, dist_data, offset_ids, counts->counts);
first_id++;
}
for(i=idS[0]; i<idS[1]; i++) {
set_interblock_counts(i, numP_other, dist_data, counts->counts);
for(i=counts->idI + first_id; i<counts->idE; i++) {
set_interblock_counts(i, numP_other, dist_data, offset_ids, counts->counts);
counts->displs[i] = counts->displs[i-1] + counts->counts[i-1];
}
free(idS);
for(i=0; i<numP_other; i++) {
if(counts->counts[i] < 0) {
fprintf(stderr, "Counts value [i=%d/%d] is negative for rank %d/%d ", i, numP_other, myId, numP);
MPI_Abort(MPI_COMM_WORLD, -3);
}
if(counts->displs[i] < 0) {
fprintf(stderr, "Displs value [i=%d/%d] is negative for rank %d/%d ", i, numP_other, myId, numP);
MPI_Abort(MPI_COMM_WORLD, -3);
}
}
}
/*
......@@ -83,12 +104,8 @@ void get_block_dist(int qty, int id, int numP, struct Dist_data *dist_data) {
dist_data->fin = (id+1) * dist_data->tamBl + rem;
}
if(dist_data->fin > qty) {
dist_data->fin = qty;
}
if(dist_data->ini > dist_data->fin) {
dist_data->ini = dist_data->fin;
}
if(dist_data->fin > qty) { dist_data->fin = qty; }
if(dist_data->ini > dist_data->fin) { dist_data->ini = dist_data->fin; }
dist_data->tamBl = dist_data->fin - dist_data->ini;
}
......@@ -98,11 +115,11 @@ void get_block_dist(int qty, int id, int numP, struct Dist_data *dist_data) {
* Obtiene para el Id de un proceso dado, cuantos elementos
* enviara o recibira desde el proceso indicado en Dist_data.
*/
void set_interblock_counts(int id, int numP, struct Dist_data data_dist, int *sendcounts) {
void set_interblock_counts(int id, int numP, struct Dist_data data_dist, int offset_ids, int *sendcounts) {
struct Dist_data other;
int biggest_ini, smallest_end;
get_block_dist(data_dist.qty, id, numP, &other);
get_block_dist(data_dist.qty, id - offset_ids, numP, &other);
// Si el rango de valores no coincide, se pasa al siguiente proceso
if(data_dist.ini >= other.fin || data_dist.fin <= other.ini) {
......@@ -110,18 +127,10 @@ void set_interblock_counts(int id, int numP, struct Dist_data data_dist, int *se
}
// Obtiene el proceso con mayor ini entre los dos procesos
if(data_dist.ini > other.ini) {
biggest_ini = data_dist.ini;
} else {
biggest_ini = other.ini;
}
biggest_ini = (data_dist.ini > other.ini) ? data_dist.ini : other.ini;
// Obtiene el proceso con menor fin entre los dos procesos
if(data_dist.fin < other.fin) {
smallest_end = data_dist.fin;
} else {
smallest_end = other.fin;
}
smallest_end = (data_dist.fin < other.fin) ? data_dist.fin : other.fin;
sendcounts[id] = smallest_end - biggest_ini; // Numero de elementos a enviar/recibir del proceso Id
}
......@@ -184,18 +193,19 @@ void get_util_ids(struct Dist_data dist_data, int numP_other, int **idS) {
* El vector displs indica los desplazamientos necesarios para cada comunicacion
* con el proceso "i" del otro grupo.
*
* El vector zero_arr se utiliza cuando se quiere indicar un vector incializado
* a 0 en todos sus elementos. Sirve para indicar que no hay comunicacion.
*/
void mallocCounts(struct Counts *counts, size_t numP) {
counts->counts = calloc(numP, sizeof(int));
if(counts->counts == NULL) { MPI_Abort(MPI_COMM_WORLD, -2);}
counts->displs = calloc(numP, sizeof(int));
if(counts->displs == NULL) { MPI_Abort(MPI_COMM_WORLD, -2);}
counts->zero_arr = calloc(numP, sizeof(int));
if(counts->zero_arr == NULL) { MPI_Abort(MPI_COMM_WORLD, -2);}
counts->len = numP;
counts->idI = -1;
counts->idE = -1;
counts->first_target_displs = -1;
}
......@@ -206,12 +216,18 @@ void mallocCounts(struct Counts *counts, size_t numP) {
* de forma dinamica.
*/
void freeCounts(struct Counts *counts) {
if(counts == NULL) {
return;
}
if(counts->counts != NULL) {
free(counts->counts);
free(counts->displs);
free(counts->zero_arr);
counts->counts = NULL;
}
if(counts->displs != NULL) {
free(counts->displs);
counts->displs = NULL;
counts->zero_arr = NULL;
}
}
/*
......
......@@ -18,12 +18,13 @@ struct Dist_data {
};
struct Counts {
int len, idI, idE;
int first_target_displs; // RMA. Indicates displacement for first target when performing a Get.
int *counts;
int *displs;
int *zero_arr;
};
void prepare_comm_alltoall(int myId, int numP, int numP_other, int n, struct Counts *counts);
void prepare_comm_alltoall(int myId, int numP, int numP_other, int n, int offset_ids, struct Counts *counts);
void prepare_comm_allgatherv(int numP, int n, struct Counts *counts);
void get_block_dist(int qty, int id, int numP, struct Dist_data *dist_data);
......
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