From bb98d65d83affe49dff1f231c999204d6ae5ca65 Mon Sep 17 00:00:00 2001
From: Rizwana Begum <rb639@drexel.edu>
Date: Tue, 5 May 2015 10:45:14 -0400
Subject: [PATCH] update

---
 figures/notuning_wtuning.py | 39 ++++++++++++++++++++++++++-------------
 1 file changed, 26 insertions(+), 13 deletions(-)

diff --git a/figures/notuning_wtuning.py b/figures/notuning_wtuning.py
index ae1a94a..b106638 100644
--- a/figures/notuning_wtuning.py
+++ b/figures/notuning_wtuning.py
@@ -63,14 +63,14 @@ def get_no_tuning_energy_performance(args, budget, bmark):
 	energy = energy/1e6
 	performance = performance/1e6 
 
-	return (energy, performance)
+	return (optimal_point, energy, performance)
 
 def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 	dir_path = args.input_dir
 	output_dir_path = args.output_dir
 
 	benchmarks, labels = get_benchmarks(args)
-#	benchmarks =['bzip2']
+#	benchmarks =['gobmk']
 	#plot constants
 	cpuflist = get_cpu_freq_plot_list(args)
 	memflist = get_mem_freq_plot_list(args)
@@ -84,7 +84,7 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 		for budget_index, budget in enumerate(budget_list):
 			print "Inefficiency Budget: "+str(budget)+" Benchmark: "+bmark
 			
-			energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
+			aggr_opt_point, energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
 			print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
 
 			bmarkDirPath = os.path.join(os.path.join(dir_path, "per_sample_data"), bmark)
@@ -123,6 +123,9 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 			memfpoints = [memf for memf in [data_to_plot[sample]["mem_freq"] for sample in range(len(data_to_plot))]]
 			samplepoints = sample_points
 
+			#print cpufpoints
+			#print memfpoints
+			#print samplepoints
 			#Total number of transitions
 			num_transitions = 0.0
 			#Available settings for (CPU, MEM)
@@ -134,6 +137,9 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 			prev_tr_sample = 0
 			energy = 0
 			performance = 0
+			aggr_energy = 0
+			aggr_performance = 0
+			idx = 0
 			while index < len( samplepoints ):
 				current_sample = samplepoints[index]
 
@@ -158,16 +164,19 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 								if point[1] > optimal_point[1]:
 									optimal_point = point
 						done = 0
-						idx = prev_tr_sample+1
-						while done == 0:
-							energy += get_energy(frontiers_data, optimal_point[0], optimal_point[1], idx)
-							performance += get_performance(frontiers_data, optimal_point[0], optimal_point[1], idx)
-							if idx == samplepoints[index-1]:
+						while done == 0 or idx == len(samplepoints) -1:
+							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
-							else: 
-								idx += 1
+							idx += 1
 
-						prev_tr_sample = samplepoints[index-1]
+						prev_tr_sample = samplepoints[index-2]
 
 				# When there are no common points, transition
 				if (len(common_points) == 0):
@@ -192,13 +201,17 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
 			performance = (performance +(num_transitions * perf_cost))/1e6 
 			energy_data[budget_index].append(energy)
 			performance_data[budget_index].append(performance)
+			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"
 
 def main(argv):
 	args = parse(argv)
 
 	for thresh in [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], thresh, 0, 0)
+#		energy_time(args, [1.0,1.1, 1.2, 1.3,1.6,3.0], thresh, 0, 0)
+
 if __name__ == "__main__":
 	main(sys.argv)
--
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