fixed no/wtuning

Rizwana Begum
1 parent bb98d65d
Showing 1 changed file with 29 additions and 15 deletions
figures/notuning_wtuning.py
@@ -38,7 +38,7 @@ def get_no_tuning_energy_performance(args, budget, bmark):
 dir_path = args.input_dir
  
 # finding points with 3% threshold of target budget/inefficiency
-	thresh = 3
+	thresh = 3 
  
 bmarkDirPath = os.path.join(os.path.join(dir_path, "aggr_data"), bmark)
 frontiers_file = os.path.join(bmarkDirPath, "frontiers.json")
@@ -70,17 +70,16 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 output_dir_path = args.output_dir
  
 benchmarks, labels = get_benchmarks(args)
-#	benchmarks =['gobmk']
+#	benchmarks = ['bzip2']
 #plot constants
 cpuflist = get_cpu_freq_plot_list(args)
 memflist = get_mem_freq_plot_list(args)
  
 # finding points with 3% threshold of target budget/inefficiency
-	thresh = 3
-	energy_data = [ [] for thresh in budget_list]
-	performance_data = [ [] for thresh in budget_list]
+	thresh = 3 
+	energy_data = [ [] for bgt in budget_list]
+	performance_data = [ [] for bgt in budget_list]
 for bmark in benchmarks:
-	data = []
 for budget_index, budget in enumerate(budget_list):
 print "Inefficiency Budget: "+str(budget)+" Benchmark: "+bmark
  
@@ -109,12 +108,19 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 if point["speedup"] > optimal_point["speedup"]:
 optimal_point = point
  
+#	if frontiers_data["data"].index(data) == 5:
+#	print filtered_data
+#	print optimal_point 
+
 local_rect_points=[]
 for point in filtered_data:
 if (optimal_point["speedup"] - point["speedup"]) < 0:
 print "something is wrong!"
  
 if (optimal_point["speedup"] - point["speedup"]) * 100 / optimal_point["speedup"] <= cluster_thresh:
+	#	if optimal_point != point:
+	#	print optimal_point
+	#	print point
 data_to_plot.append(point)
 sample_points.append(frontiers_data["data"].index(data))
 local_rect_points.append(point)
@@ -145,13 +151,16 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
  
 #Construct the current settings
 current_settings = Set()
+	#print "current sample: "+str(current_sample)
 while index < len( samplepoints ) and samplepoints[index] == current_sample:
+	#print "index: "+str(index)
 current_settings.add((cpufpoints[index],memfpoints[index]))
 index = index + 1
  
 #Compute the common points between current and what is available
 common_points = current_settings.intersection(settings_available)
  
+	#print "sp = " + str(samplepoints[-1])
 if (len(common_points) == 0 or index == len( samplepoints )):
 # find the point with highest cpu and mem freq
 if (current_sample !=0 ):
@@ -164,20 +173,26 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 if point[1] > optimal_point[1]:
 optimal_point = point
 done = 0
-	while done == 0 or idx == len(samplepoints) -1:
+	#print samplepoints[-1]
+	while done == 0 or idx == samplepoints[-1]:
+	#print idx
 energy += get_energy(frontiers_data,optimal_point[0], optimal_point[1], idx)
 performance += get_performance(frontiers_data,optimal_point[0], optimal_point[1], idx)
 aggr_energy += get_energy(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
 aggr_performance += get_performance(frontiers_data,	aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
 if aggr_energy < energy:
 print "unexpected!"
-	#	print "("+str(optimal_point[0])+", "+str(optimal_point[1])+", "+str(energy)+", "+str(performance)+") "+"("+str(aggr_opt_point["cpu_freq"])+", "+str(aggr_opt_point["mem_freq"])+", "+str(aggr_energy)+", "+str(aggr_performance)+") "
-	if idx == samplepoints[index-2]:
-	done = 1
+	#	print "("+str(optimal_point[0])+", "+str(optimal_point[1])+", "+str(energy)+", "+str(performance)+") "+"("+str(aggr_opt_point["cpu_freq"])+", "+str(aggr_opt_point["mem_freq"])+", "+str(aggr_energy)+", "+str(aggr_performance)+") --- " + str((energy - aggr_energy) * 100 / aggr_energy) +" " +str((performance - aggr_performance) * 100 / aggr_performance)
+	if index < len(samplepoints):
+	if idx == samplepoints[index]-2:
+	done = 1
+	prev_tr_sample = samplepoints[index]-2
+	else:
+	if idx == samplepoints[-2]:
+	done = 1
+	prev_tr_sample = samplepoints[-2]
 idx += 1
  
-	prev_tr_sample = samplepoints[index-2]
-
 # When there are no common points, transition
 if (len(common_points) == 0):
 settings_available = current_settings #all current settings are now available
@@ -204,14 +219,13 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 aggr_energy = (aggr_energy + (num_transitions * energy_cost))/1e6
 aggr_performance = (aggr_performance +(num_transitions * perf_cost))/1e6 
 print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
-	print "w.tuning: performance (ms): "+str(performance)+" energy(mJ): "+str(energy) +"\n"
+	print "w.tuning: performance (ms): "+str(performance)+" energy(mJ): "+str(energy) + " "+ str((energy - aggr_energy) * 100 / aggr_energy) +"% " +str((performance - aggr_performance) * 100 / aggr_performance)+"%\n"
  
 def main(argv):
 args = parse(argv)
  
 for thresh in [0.0]:
-	energy_time(args, [1.0], thresh, 0, 0)
-#	energy_time(args, [1.0,1.1, 1.2, 1.3,1.6,3.0], thresh, 0, 0)
+	energy_time(args, [1.0,1.1,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,2.0,3.0], thresh, 0, 0)
  
 if __name__ == "__main__":
 main(sys.argv)