blue / papers.iiswc2015-frontiers · Commits

Commit bb98d65d83affe49dff1f231c999204d6ae5ca65

Authored by Rizwana Begum
1 parent 9bb9ab8f

update

Inline Side-by-side
Showing 1 changed file with 26 additions and 13 deletions
figures/notuning_wtuning.py
  View file @bb98d65
... ... @@ -63,14 +63,14 @@ def get_no_tuning_energy_performance(args, budget, bmark):
63 63 energy = energy/1e6
64 64 performance = performance/1e6
65 65  
66   - return (energy, performance)
  66 + return (optimal_point, energy, performance)
67 67  
68 68 def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
69 69 dir_path = args.input_dir
70 70 output_dir_path = args.output_dir
71 71  
72 72 benchmarks, labels = get_benchmarks(args)
73   -# benchmarks =['bzip2']
  73 +# benchmarks =['gobmk']
74 74 #plot constants
75 75 cpuflist = get_cpu_freq_plot_list(args)
76 76 memflist = get_mem_freq_plot_list(args)
... ... @@ -84,7 +84,7 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
84 84 for budget_index, budget in enumerate(budget_list):
85 85 print "Inefficiency Budget: "+str(budget)+" Benchmark: "+bmark
86 86  
87   - energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
  87 + aggr_opt_point, energy_notuning, performance_notuning = get_no_tuning_energy_performance(args, budget, bmark)
88 88 print "no.tuning: performance (ms): "+str(performance_notuning)+" energy(mJ): "+str(energy_notuning)
89 89  
90 90 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):
123 123 memfpoints = [memf for memf in [data_to_plot[sample]["mem_freq"] for sample in range(len(data_to_plot))]]
124 124 samplepoints = sample_points
125 125  
  126 + #print cpufpoints
  127 + #print memfpoints
  128 + #print samplepoints
126 129 #Total number of transitions
127 130 num_transitions = 0.0
128 131 #Available settings for (CPU, MEM)
... ... @@ -134,6 +137,9 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
134 137 prev_tr_sample = 0
135 138 energy = 0
136 139 performance = 0
  140 + aggr_energy = 0
  141 + aggr_performance = 0
  142 + idx = 0
137 143 while index < len( samplepoints ):
138 144 current_sample = samplepoints[index]
139 145  
... ... @@ -158,16 +164,19 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
158 164 if point[1] > optimal_point[1]:
159 165 optimal_point = point
160 166 done = 0
161   - idx = prev_tr_sample+1
162   - while done == 0:
163   - energy += get_energy(frontiers_data, optimal_point[0], optimal_point[1], idx)
164   - performance += get_performance(frontiers_data, optimal_point[0], optimal_point[1], idx)
165   - if idx == samplepoints[index-1]:
  167 + while done == 0 or idx == len(samplepoints) -1:
  168 + energy += get_energy(frontiers_data,optimal_point[0], optimal_point[1], idx)
  169 + performance += get_performance(frontiers_data,optimal_point[0], optimal_point[1], idx)
  170 + aggr_energy += get_energy(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
  171 + aggr_performance += get_performance(frontiers_data, aggr_opt_point["cpu_freq"], aggr_opt_point["mem_freq"], idx)
  172 + if aggr_energy < energy:
  173 + print "unexpected!"
  174 + # 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)+") "
  175 + if idx == samplepoints[index-2]:
166 176 done = 1
167   - else:
168   - idx += 1
  177 + idx += 1
169 178  
170   - prev_tr_sample = samplepoints[index-1]
  179 + prev_tr_sample = samplepoints[index-2]
171 180  
172 181 # When there are no common points, transition
173 182 if (len(common_points) == 0):
... ... @@ -192,13 +201,17 @@ def energy_time(args, budget_list, cluster_thresh, perf_cost, energy_cost):
192 201 performance = (performance +(num_transitions * perf_cost))/1e6
193 202 energy_data[budget_index].append(energy)
194 203 performance_data[budget_index].append(performance)
  204 + aggr_energy = (aggr_energy + (num_transitions * energy_cost))/1e6
  205 + aggr_performance = (aggr_performance +(num_transitions * perf_cost))/1e6
  206 + print "no.tuning(cum): performance (ms): "+str(aggr_performance)+"energy(mJ): "+str(aggr_energy)
195 207 print "w.tuning: performance (ms): "+str(performance)+" energy(mJ): "+str(energy) +"\n"
196 208  
197 209 def main(argv):
198 210 args = parse(argv)
199 211  
200 212 for thresh in [0.0]:
201   - energy_time(args, [1.0,1.1, 1.2, 1.3,1.6,3.0], thresh, 0, 0)
202   -
  213 + energy_time(args, [1.0], thresh, 0, 0)
  214 +# energy_time(args, [1.0,1.1, 1.2, 1.3,1.6,3.0], thresh, 0, 0)
  215 +
203 216 if __name__ == "__main__":
204 217 main(sys.argv)
... ...