RMA functionality and refactor of many of the codes

Analysis/CreateIterDataframe.py

+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)
+

Analysis/CreateResizeDataframe.py

+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)

Analysis/MallTimes.py

@@ -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')

Analysis/bt_scheme.py

+'''
+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)

Analysis/iterTimes.py

-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')

Analysis/joinDf.py

@@ -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')

Codes/IOcodes/read_ini.c

@@ -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)) {

Codes/IOcodes/results.c

@@ -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);

Codes/IOcodes/results.h

@@ -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;

Codes/Main/Main.c

@@ -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);

Codes/Main/Main_datatypes.h

@@ -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;

Codes/Main/configuration.c

@@ -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);
   }
 }

Codes/Makefile

 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 =
 

Codes/malleability/CommDist.h

@@ -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

Codes/malleability/distribution_methods/block_distribution.c

@@ -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;
+    }
 }
 
 /*

Codes/malleability/distribution_methods/block_distribution.h

@@ -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);