Commit b6dc95b1d45bc9153ae7d49eb92f295ac73c48c1

Authored by Rizwana Begum
1 parent 40efbe7a

updated

figures/energy_perf_bar.py
... ... @@ -35,10 +35,10 @@ def plot_energy_perf_bar(args, threshold_list, budget):
35 35  
36 36 # finding points with 3% threshold of target budget/inefficiency
37 37 thresh = 3
38   - energy_bar_data = [ [] for thresh in threshold_list]
39   - performance_bar_data = [ [] for thresh in threshold_list]
40   - energy_bar_data_nocost = [ [] for thresh in threshold_list]
41   - performance_bar_data_nocost = [ [] for thresh in threshold_list]
  38 + energy_bar_data = [ [] for thr in threshold_list]
  39 + performance_bar_data = [ [] for thr in threshold_list]
  40 + energy_bar_data_nocost = [ [] for thr in threshold_list]
  41 + performance_bar_data_nocost = [ [] for thr in threshold_list]
42 42  
43 43 print budget
44 44 for threshold_index, cluster_thresh in enumerate(threshold_list):
... ... @@ -268,8 +268,8 @@ def plot_abs_energy_time_bar(args, budget_list, cluster_thresh, perf_cost, energ
268 268  
269 269 # finding points with 3% threshold of target budget/inefficiency
270 270 thresh = 3
271   - energy_bar_data = [ [] for thresh in budget_list]
272   - performance_bar_data = [ [] for thresh in budget_list]
  271 + energy_bar_data = [ [] for thr in budget_list]
  272 + performance_bar_data = [ [] for thr in budget_list]
273 273 for budget_index, budget in enumerate(budget_list):
274 274 data = []
275 275 for bmark in benchmarks:
... ...
figures/notuning_wtuning.py
... ... @@ -84,7 +84,7 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
84 84 print "Inefficiency Budget: "+str(budget)+" Benchmark: "+bmark
85 85  
86 86 aggr_opt_point, energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
87   - print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
  87 + #print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
88 88  
89 89 bmarkDirPath = os.path.join(os.path.join(dir_path, "per_sample_data"), bmark)
90 90 frontiers_file = os.path.join(bmarkDirPath, "per_sample_frontiers.json")
... ... @@ -180,8 +180,8 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
180 180 performance += get_performance(frontiers_data,optimal_point[0], optimal_point[1], idx)
181 181 aggr_energy += get_energy(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
182 182 aggr_performance += get_performance(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
183   - if aggr_energy < energy:
184   - print "unexpected!"
  183 +# if aggr_energy < energy:
  184 +# print "unexpected!"
185 185 # 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)
186 186 if index < len(samplepoints):
187 187 if idx == samplepoints[index]-2:
... ... @@ -218,8 +218,9 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
218 218 performance_data[budget_index].append(performance)
219 219 aggr_energy = (aggr_energy + (num_transitions * energy_cost))/1e6
220 220 aggr_performance = (aggr_performance +(num_transitions * perf_cost))/1e6
221   - print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
222   - 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"
  221 + #print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
  222 + #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"
  223 + print "w.tuning: energy: "+ str(((energy - aggr_energy) * 10000 / aggr_energy)/100) +"% execution time:" +str(((performance - aggr_performance) * 10000 / aggr_performance)/100)+"%\n"
223 224  
224 225 def main(argv):
225 226 args = parse(argv)
... ...
figures/stable_length_box_thresholds.py
... ... @@ -23,7 +23,7 @@ def plot_stable_length_box(args, threshold_list, budget_list):
23 23 # finding points with 3% threshold of target budget/inefficiency
24 24 thresh = 3
25 25 for bmark in benchmarks:
26   - box_data = [ [] for thresh in threshold_list]
  26 + box_data = [ [] for thr in threshold_list]
27 27 for threshold_index, cluster_thresh in enumerate(threshold_list):
28 28 data = []
29 29 for budget in budget_list:
... ...
figures/stable_line.py
... ... @@ -411,7 +411,7 @@ def plot_stable_length_box_across_thresholds(args, threshold_list, budget):
411 411  
412 412 # finding points with 3% threshold of target budget/inefficiency
413 413 thresh = 3
414   - box_data = [ [] for thresh in threshold_list]
  414 + box_data = [ [] for thr in threshold_list]
415 415 for threshold_index, cluster_thresh in enumerate(threshold_list):
416 416 data = []
417 417 for bmark in benchmarks:
... ...