- Timestamp:
- Feb 16, 2017, 3:51:52 PM (7 years ago)
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trunk/platforms/tsar_generic_xbar/scripts/create_graphs.py
r1012 r1048 7 7 8 8 9 apps = [ 'blackscholes', 'filt_ga', 'fft_ga', 'histo-opt', 'kmeans-opt', 'linear_regression', 'lu', 'mandel', 'pca-opt', 'radix_ga', 'string_match' ] 10 #apps = [ 'blackscholes', 'fft_ga', 'filt_ga', 'histo-opt', 'kmeans-opt', 'linear_regression', 'lu', 'mandel', 'pca-opt', 'radix_ga' ] 9 11 #apps = [ 'histo-opt', 'mandel', 'filt_ga', 'radix_ga', 'fft_ga', 'pca-opt', 'fft', 'radix', 'filter', 'kmeans-opt' ] 10 apps = [ 'fft_ga', 'filt_ga', 'lu', 'radix_ga', 'histo-opt', 'mandel', 'pca-opt', 'kmeans-opt' ]11 12 #apps = [ 'histogram', 'mandel', 'filter', 'fft', 'fft_ga', 'filt_ga', 'pca', 'lu' ] # radix radix_ga kmeans 12 #apps = [ 'histo-opt', 'histogram2', 'histo-opt2' ] 13 #nb_procs = [ 1, 4, 8, 16, 32, 64, 128, 256 ] 13 #apps = [ 'fal_sh_2' ] 14 14 nb_procs = [ 1, 4, 8, 16, 32, 64, 128, 256 ] 15 single_protocols = ['dhccp', 'hmesi'] 16 joint_protocols = ['dhccp', 'hmesi'] 15 #nb_procs = [ 256 ] 16 single_protocols = ['dhccp', 'th0', 'hmesi', 'wtidl'] 17 joint_protocols = ['dhccp', 'th0', 'hmesi', 'wtidl' ] 17 18 #joint_protocols = [] 18 19 … … 31 32 log_term_name = '_term_' 32 33 33 coherence_tmpl = os.path.join(scripts_path, template_dir, 'coherence_template.gp') # 1 graph per appli 34 speedup_tmpl = os.path.join(scripts_path, template_dir, 'speedup_template.gp') 35 metric_tmpl = os.path.join(scripts_path, template_dir, 'metric_template.gp') # 1 graph per metric 36 stacked_tmpl = os.path.join(scripts_path, template_dir, 'stacked_template.gp') 34 coherence_tmpl = os.path.join(scripts_path, template_dir, 'coherence_template.gp') # 1 graph per appli 35 speedup_tmpl = os.path.join(scripts_path, template_dir, 'speedup_template.gp') 36 metric_tmpl = os.path.join(scripts_path, template_dir, 'metric_template.gp') # 1 graph per metric 37 stacked_tmpl = os.path.join(scripts_path, template_dir, 'stacked_template.gp') 38 cst_exec_time_tmpl = os.path.join(scripts_path, template_dir, 'cst_exec_time_template.gp') 37 39 38 40 … … 140 142 metrics_val[prot][app][i]['direct_cost'] = metrics_val[prot][app][i]['read_cost'] + metrics_val[prot][app][i]['write_cost'] 141 143 metrics_val[prot][app][i]['broadcast_cost'] = metrics_val[prot][app][i]['broadcast'] * 2 * (x * y - 1) 142 metrics_val[prot][app][i]['coherence_cost'] = metrics_val[prot][app][i]['broadcast_cost'] + metrics_val[prot][app][i]['m_inv_cost'] + metrics_val[prot][app][i]['update_cost'] 144 #metrics_val[prot][app][i]['coherence_cost'] = metrics_val[prot][app][i]['broadcast_cost'] + metrics_val[prot][app][i]['m_inv_cost'] + metrics_val[prot][app][i]['update_cost'] 145 metrics_val[prot][app][i]['coherence_cost'] = metrics_val[prot][app][i]['broadcast_cost'] + metrics_val[prot][app][i]['m_inv_cost'] + metrics_val[prot][app][i]['update_cost'] + metrics_val[prot][app][i]['cleanup_cost'] + metrics_val[prot][app][i]['cleanup_d_cost'] + metrics_val[prot][app][i]['inval_ro_cost'] 143 146 if metrics_val[prot][app][i]['broadcast'] < metrics_val[prot][app][i]['write_broadcast']: 144 147 # test to patch a bug in mem_cache … … 159 162 subprocess.call([ 'mkdir', '-p', os.path.join(scripts_path, graph_dir) ]) 160 163 161 ############################################################ 162 ### Graph 1 : Coherence traffic Cost per application ### 163 ############################################################ 164 165 for prot in single_protocols: 166 for app in apps: 167 data_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.dat') 168 gp_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.gp') 169 170 # Creating the data file 171 width = 15 172 content = "" 173 174 for metric in [ '#nb_procs' ] + grouped_metrics: 175 content += metric + " " 176 nb_spaces = width - len(metric) 177 content += nb_spaces * ' ' 178 content += "\n" 179 180 for i in nb_procs: 181 content += "%-15d " % i 182 for metric in grouped_metrics: 183 val = float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000 184 content += "%-15f " % val 185 content += "\n" 186 187 create_file(data_coherence_name, content) 188 189 # Creating the gp file 190 template_file = open(coherence_tmpl, 'r') 191 template = template_file.read() 192 193 plot_str = "" 194 col = 2 195 for metric in grouped_metrics: 196 if metric != grouped_metrics[0]: 197 plot_str += ", \\\n " 198 plot_str += "\"" + data_coherence_name + "\" using ($1):($" + str(col) + ") lc rgb " + colors[col - 2] + " title \"" + m_metric_name[metric] + "\" with linespoint" 199 col += 1 200 gp_commands = template % dict(app_name = m_app_name[app], nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + app + '_coherence')) 201 202 create_file(gp_coherence_name, gp_commands) 203 204 # Calling gnuplot 205 print "gnuplot", gp_coherence_name 206 subprocess.call([ 'gnuplot', gp_coherence_name ]) 207 208 209 ############################################################ 210 ### Graph 2 : Speedup per Application ### 211 ############################################################ 212 213 for prot in single_protocols: 214 for app in apps: 215 216 data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.dat') 217 gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.gp') 218 219 # Creating data file 220 width = 15 221 content = "#nb_procs" 222 nb_spaces = width - len(content) 223 content += nb_spaces * ' ' 224 content += "speedup\n" 225 226 for i in nb_procs: 227 content += "%-15d " % i 228 val = exec_time[prot][app][i] 229 content += "%-15f\n" % (exec_time[prot][app][1] / float(val)) 230 231 plot_str = "\"" + data_speedup_name + "\" using ($1):($2) lc rgb \"#654387\" title \"Speedup\" with linespoint" 232 233 create_file(data_speedup_name, content) 234 235 # Creating the gp file 236 template_file = open(speedup_tmpl, 'r') 237 template = template_file.read() 238 239 gp_commands = template % dict(appli = m_app_name[app], nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + app + '_speedup')) 240 241 create_file(gp_speedup_name, gp_commands) 242 243 # Calling gnuplot 244 print "gnuplot", gp_speedup_name 245 subprocess.call([ 'gnuplot', gp_speedup_name ]) 246 247 248 ############################################################ 249 ### Graph 3 : All speedups on the same Graph ### 250 ############################################################ 251 252 for prot in single_protocols: 253 # This graph uses the same template as the graph 2 254 data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.dat') 255 gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.gp') 256 257 # Creating data file 258 width = 15 259 content = "#nb_procs" 260 nb_spaces = width - len(content) 261 content += (nb_spaces + 1) * ' ' 262 for app in apps: 263 content += app + " " 264 content += (width - len(app)) * " " 265 content += "\n" 266 267 for i in nb_procs: 268 content += "%-15d " % i 269 for app in apps: 270 val = exec_time[prot][app][i] 271 content += "%-15f " % (exec_time[prot][app][1] / float(val)) 272 content += "\n" 273 274 create_file(data_speedup_name, content) 275 276 # Creating gp file 277 template_file = open(speedup_tmpl, 'r') 278 template = template_file.read() 279 280 plot_str = "" 281 col = 2 282 for app in apps: 283 if app != apps[0]: 284 plot_str += ", \\\n " 285 plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_app_name[app] + "\" with linespoint" 286 col += 1 287 288 gp_commands = template % dict(appli = "All Applications", nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_all_speedup')) 289 290 create_file(gp_speedup_name, gp_commands) 291 292 # Calling gnuplot 293 print "gnuplot", gp_speedup_name 294 subprocess.call([ 'gnuplot', gp_speedup_name ]) 295 296 297 ############################################################ 298 ### Graph 4 : Graph per metric ### 299 ############################################################ 300 301 # The following section creates the graphs grouped by measure (e.g. #broadcasts) 302 # The template file cannot be easily created otherwise it would not be generic 303 # in many ways. This is why it is mainly created here. 304 # Graphs are created for metric in the "individual_metrics" list 305 306 for prot in single_protocols: 307 for metric in individual_metrics: 308 data_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.dat') 309 gp_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.gp') 310 311 # Creating the gp file 312 # Setting xtics, i.e. number of procs for each application 313 xtics_str = "(" 314 first = True 315 xpos = 1 316 app_labels = "" 317 for num_appli in range(0, len(apps)): 318 for i in nb_procs: 319 if not first: 320 xtics_str += ", " 321 first = False 322 if i == nb_procs[0]: 323 xpos_first = xpos 324 xtics_str += "\"%d\" %.1f" % (i, xpos) 325 xpos_last = xpos 326 xpos += 1.5 327 xpos += 0.5 328 app_name_xpos = float((xpos_first + xpos_last)) / 2 329 app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 330 xtics_str += ")" 331 332 xmax_val = float(xpos - 1) 333 334 # Writing the lines of "plot" 335 plot_str = "" 336 xpos = 0 337 first = True 338 column = 2 339 for i in range(0, len(nb_procs)): 340 if not first: 341 plot_str += ", \\\n " 342 first = False 343 plot_str += "\"%s\" using ($1+%.1f):($%d) lc rgb %s notitle with boxes" % (data_metric_name, xpos, column, colors[i]) 344 column += 1 345 xpos += 1.5 346 347 template_file = open(metric_tmpl, 'r') 348 template = template_file.read() 349 350 gp_commands = template % dict(xtics_str = xtics_str, app_labels = app_labels, ylabel_str = m_metric_name[metric], norm_factor_str = m_norm_factor_name[m_metric_norm[metric]], xmax_val = xmax_val, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + metric)) 351 352 create_file(gp_metric_name, gp_commands) 353 354 # Creating the data file 355 width = 15 356 content = "#x_pos" 357 nb_spaces = width - len(content) 358 content += nb_spaces * ' ' 359 for i in nb_procs: 360 content += "%-15d" % i 361 content += "\n" 362 363 x_pos = 1 364 for app in apps: 365 # Computation of x_pos 366 content += "%-15f" % x_pos 367 x_pos += len(nb_procs) * 1.5 + 0.5 368 for i in nb_procs: 369 if m_metric_norm[metric] == "N": 370 content += "%-15d" % (metrics_val[prot][app][i][metric]) 371 elif m_metric_norm[metric] == "P": 372 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / i) 373 elif m_metric_norm[metric] == "C": 374 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000) 375 elif m_metric_norm[metric] == "W": 376 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_write'])) # Number of writes 377 elif m_metric_norm[metric] == "R": 378 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_read'])) # Number of reads 379 elif m_metric_norm[metric] == "D": 380 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_direct'])) # Number of req. 381 elif is_numeric(m_metric_norm[metric]): 382 content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][int(m_metric_norm[metric])][metric])) 383 else: 384 assert(False) 385 386 app_name = m_app_name[app] 387 content += "#" + app_name + "\n" 388 389 create_file(data_metric_name, content) 390 391 # Calling gnuplot 392 print "gnuplot", gp_metric_name 393 subprocess.call([ 'gnuplot', gp_metric_name ]) 394 395 396 ############################################################ 397 ### Graph 5 : Stacked histogram with counters ### 398 ############################################################ 399 400 # The following section creates a stacked histogram containing 401 # the metrics in the "stacked_metric" list 402 # It is normalized per application w.r.t the values on 256 procs 403 404 for prot in single_protocols: 405 data_stacked_name = os.path.join(scripts_path, gen_dir, prot + '_stacked.dat') 406 gp_stacked_name = os.path.join(scripts_path, gen_dir, prot + '_stacked.gp') 407 408 norm_factor_value = nb_procs[-1] 409 410 # Creating the gp file 411 template_file = open(stacked_tmpl, 'r') 412 template = template_file.read() 413 414 xtics_str = "(" 415 first = True 416 xpos = 1 417 app_labels = "" 418 for num_appli in range(0, len(apps)): 419 for i in nb_procs[1:len(nb_procs)]: # skipping values for 1 proc 420 if not first: 421 xtics_str += ", " 422 first = False 423 if i == nb_procs[1]: 424 xpos_first = xpos 425 xtics_str += "\"%d\" %d -1" % (i, xpos) 426 xpos_last = xpos 427 xpos += 1 428 xpos += 1 429 app_name_xpos = float((xpos_first + xpos_last)) / 2 430 app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 431 xtics_str += ")" 432 433 plot_str = "newhistogram \"\"" 434 n = 1 435 for stacked_metric in stacked_metrics: 436 plot_str += ", \\\n " + "'" + data_stacked_name + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[stacked_metric] + "\"" 437 n += 1 438 439 ylabel_str = "Breakdown of Coherence Traffic Normalized w.r.t. \\nthe Values on %d Processors" % norm_factor_value 440 content = template % dict(svg_name = os.path.join(graph_dir, prot + '_stacked'), xtics_str = xtics_str, plot_str = plot_str, ylabel_str = ylabel_str, app_labels = app_labels, prot_labels = "") 441 442 create_file(gp_stacked_name, content) 443 444 # Creating the data file 445 # Values are normalized by application, w.r.t. the number of requests for a given number of procs 446 content = "#" 447 for stacked_metric in stacked_metrics: 448 content += stacked_metric 449 content += ' ' + ' ' * (15 - len(stacked_metric)) 450 content += "\n" 451 for app in apps: 452 if app != apps[0]: 453 for i in range(0, len(stacked_metrics)): 454 content += "%-15f" % 0.0 455 content += "\n" 456 for i in nb_procs[1:len(nb_procs)]: 457 for stacked_metric in stacked_metrics: 458 metric_val = metrics_val[prot][app][norm_factor_value]['total_stacked'] # Normalisation 459 if metric_val != 0: 460 content += "%-15f" % (float(metrics_val[prot][app][i][stacked_metric]) / metric_val) 461 else: 462 content += "%-15f" % 0 463 content += "\n" 464 465 create_file(data_stacked_name, content) 466 # Calling gnuplot 467 print "gnuplot", gp_stacked_name 468 subprocess.call([ 'gnuplot', gp_stacked_name ]) 164 ############################################################# 165 #### Graph 1 : Coherence traffic Cost per application ### 166 ############################################################# 167 # 168 #for prot in single_protocols: 169 # for app in apps: 170 # data_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.dat') 171 # gp_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.gp') 172 # 173 # # Creating the data file 174 # width = 15 175 # content = "" 176 # 177 # for metric in [ '#nb_procs' ] + grouped_metrics: 178 # content += metric + " " 179 # nb_spaces = width - len(metric) 180 # content += nb_spaces * ' ' 181 # content += "\n" 182 # 183 # for i in nb_procs: 184 # content += "%-15d " % i 185 # for metric in grouped_metrics: 186 # #print "app : %s - prot : %s - i : %d" % (app, prot, i) 187 # val = float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000 188 # content += "%-15f " % val 189 # content += "\n" 190 # 191 # create_file(data_coherence_name, content) 192 # 193 # # Creating the gp file 194 # template_file = open(coherence_tmpl, 'r') 195 # template = template_file.read() 196 # 197 # plot_str = "" 198 # col = 2 199 # for metric in grouped_metrics: 200 # if metric != grouped_metrics[0]: 201 # plot_str += ", \\\n " 202 # plot_str += "\"" + data_coherence_name + "\" using ($1):($" + str(col) + ") lc rgb " + colors[col - 2] + " title \"" + m_metric_name[metric] + "\" with linespoint" 203 # col += 1 204 # gp_commands = template % dict(app_name = m_app_name[app], nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + app + '_coherence')) 205 # 206 # create_file(gp_coherence_name, gp_commands) 207 # 208 # # Calling gnuplot 209 # print "gnuplot", gp_coherence_name 210 # subprocess.call([ 'gnuplot', gp_coherence_name ]) 211 # 212 # 213 ############################################################# 214 #### Graph 2 : Speedup per Application ### 215 ############################################################# 216 # 217 #if 1 in nb_procs: 218 # for prot in single_protocols: 219 # for app in apps: 220 # 221 # data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.dat') 222 # gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.gp') 223 # 224 # # Creating data file 225 # width = 15 226 # content = "#nb_procs" 227 # nb_spaces = width - len(content) 228 # content += nb_spaces * ' ' 229 # content += "speedup\n" 230 # 231 # for i in nb_procs: 232 # content += "%-15d " % i 233 # val = exec_time[prot][app][i] 234 # content += "%-15f\n" % (exec_time[prot][app][1] / float(val)) 235 # 236 # plot_str = "\"" + data_speedup_name + "\" using ($1):($2) lc rgb \"#654387\" title \"Speedup\" with linespoint" 237 # 238 # create_file(data_speedup_name, content) 239 # 240 # # Creating the gp file 241 # template_file = open(speedup_tmpl, 'r') 242 # template = template_file.read() 243 # 244 # gp_commands = template % dict(appli = m_app_name[app], nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + app + '_speedup')) 245 # 246 # create_file(gp_speedup_name, gp_commands) 247 # 248 # # Calling gnuplot 249 # print "gnuplot", gp_speedup_name 250 # subprocess.call([ 'gnuplot', gp_speedup_name ]) 251 # 252 # 253 ############################################################# 254 #### Graph 3 : All speedups on the same Graph ### 255 ############################################################# 256 # 257 #if 1 in nb_procs: 258 # for prot in single_protocols: 259 # # This graph uses the same template as the graph 2 260 # data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.dat') 261 # gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.gp') 262 # 263 # # Creating data file 264 # width = 15 265 # content = "#nb_procs" 266 # nb_spaces = width - len(content) 267 # content += (nb_spaces + 1) * ' ' 268 # for app in apps: 269 # content += app + " " 270 # content += (width - len(app)) * " " 271 # content += "\n" 272 # 273 # for i in nb_procs: 274 # content += "%-15d " % i 275 # for app in apps: 276 # val = exec_time[prot][app][i] 277 # content += "%-15f " % (exec_time[prot][app][1] / float(val)) 278 # content += "\n" 279 # 280 # create_file(data_speedup_name, content) 281 # 282 # # Creating gp file 283 # template_file = open(speedup_tmpl, 'r') 284 # template = template_file.read() 285 # 286 # plot_str = "" 287 # col = 2 288 # for app in apps: 289 # if app != apps[0]: 290 # plot_str += ", \\\n " 291 # plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_app_name[app] + "\" with linespoint" 292 # col += 1 293 # 294 # gp_commands = template % dict(appli = "All Applications", nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_all_speedup')) 295 # 296 # create_file(gp_speedup_name, gp_commands) 297 # 298 # # Calling gnuplot 299 # print "gnuplot", gp_speedup_name 300 # subprocess.call([ 'gnuplot', gp_speedup_name ]) 301 # 302 # 303 ############################################################# 304 #### Graph 4 : Graph per metric ### 305 ############################################################# 306 # 307 ## The following section creates the graphs grouped by measure (e.g. #broadcasts) 308 ## The template file cannot be easily created otherwise it would not be generic 309 ## in many ways. This is why it is mainly created here. 310 ## Graphs are created for metric in the "individual_metrics" list 311 # 312 #for prot in single_protocols: 313 # for metric in individual_metrics: 314 # data_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.dat') 315 # gp_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.gp') 316 # 317 # # Creating the gp file 318 # # Setting xtics, i.e. number of procs for each application 319 # xtics_str = "(" 320 # first = True 321 # xpos = 1 322 # app_labels = "" 323 # for num_appli in range(0, len(apps)): 324 # for i in nb_procs: 325 # if not first: 326 # xtics_str += ", " 327 # first = False 328 # if i == nb_procs[0]: 329 # xpos_first = xpos 330 # xtics_str += "\"%d\" %.1f" % (i, xpos) 331 # xpos_last = xpos 332 # xpos += 1.5 333 # xpos += 0.5 334 # app_name_xpos = float((xpos_first + xpos_last)) / 2 335 # app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 336 # xtics_str += ")" 337 # 338 # xmax_val = float(xpos - 1) 339 # 340 # # Writing the lines of "plot" 341 # plot_str = "" 342 # xpos = 0 343 # first = True 344 # column = 2 345 # for i in range(0, len(nb_procs)): 346 # if not first: 347 # plot_str += ", \\\n " 348 # first = False 349 # plot_str += "\"%s\" using ($1+%.1f):($%d) lc rgb %s notitle with boxes" % (data_metric_name, xpos, column, colors[i]) 350 # column += 1 351 # xpos += 1.5 352 # 353 # template_file = open(metric_tmpl, 'r') 354 # template = template_file.read() 355 # 356 # gp_commands = template % dict(xtics_str = xtics_str, app_labels = app_labels, ylabel_str = m_metric_name[metric], norm_factor_str = m_norm_factor_name[m_metric_norm[metric]], xmax_val = xmax_val, plot_str = plot_str, svg_name = os.path.join(graph_dir, prot + '_' + metric)) 357 # 358 # create_file(gp_metric_name, gp_commands) 359 # 360 # # Creating the data file 361 # width = 15 362 # content = "#x_pos" 363 # nb_spaces = width - len(content) 364 # content += nb_spaces * ' ' 365 # for i in nb_procs: 366 # content += "%-15d" % i 367 # content += "\n" 368 # 369 # x_pos = 1 370 # for app in apps: 371 # # Computation of x_pos 372 # content += "%-15f" % x_pos 373 # x_pos += len(nb_procs) * 1.5 + 0.5 374 # for i in nb_procs: 375 # if m_metric_norm[metric] == "N": 376 # content += "%-15d" % (metrics_val[prot][app][i][metric]) 377 # elif m_metric_norm[metric] == "P": 378 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / i) 379 # elif m_metric_norm[metric] == "C": 380 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000) 381 # elif m_metric_norm[metric] == "W": 382 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_write'])) # Number of writes 383 # elif m_metric_norm[metric] == "R": 384 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_read'])) # Number of reads 385 # elif m_metric_norm[metric] == "D": 386 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][i]['total_direct'])) # Number of req. 387 # elif is_numeric(m_metric_norm[metric]): 388 # content += "%-15f" % (float(metrics_val[prot][app][i][metric]) / float(metrics_val[prot][app][int(m_metric_norm[metric])][metric])) 389 # else: 390 # assert(False) 391 # 392 # app_name = m_app_name[app] 393 # content += "#" + app_name + "\n" 394 # 395 # create_file(data_metric_name, content) 396 # 397 # # Calling gnuplot 398 # print "gnuplot", gp_metric_name 399 # subprocess.call([ 'gnuplot', gp_metric_name ]) 400 # 401 # 402 ############################################################# 403 #### Graph 5 : Stacked histogram with counters ### 404 ############################################################# 405 # 406 ## The following section creates a stacked histogram containing 407 ## the metrics in the "stacked_metric" list 408 ## It is normalized per application w.r.t the values on 256 procs 409 # 410 #for prot in single_protocols: 411 # data_stacked_name = os.path.join(scripts_path, gen_dir, prot + '_stacked.dat') 412 # gp_stacked_name = os.path.join(scripts_path, gen_dir, prot + '_stacked.gp') 413 # 414 # norm_factor_value = nb_procs[-1] 415 # 416 # # Creating the gp file 417 # template_file = open(stacked_tmpl, 'r') 418 # template = template_file.read() 419 # 420 # xtics_str = "(" 421 # first = True 422 # xpos = 1 423 # app_labels = "" 424 # for num_appli in range(0, len(apps)): 425 # for i in nb_procs[1:len(nb_procs)]: # skipping values for 1 proc 426 # if not first: 427 # xtics_str += ", " 428 # first = False 429 # if i == nb_procs[1]: 430 # xpos_first = xpos 431 # xtics_str += "\"%d\" %d -1" % (i, xpos) 432 # xpos_last = xpos 433 # xpos += 1 434 # xpos += 1 435 # app_name_xpos = float((xpos_first + xpos_last)) / 2 436 # app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 437 # xtics_str += ")" 438 # 439 # plot_str = "newhistogram \"\"" 440 # n = 1 441 # for stacked_metric in stacked_metrics: 442 # plot_str += ", \\\n " + "'" + data_stacked_name + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[stacked_metric] + "\"" 443 # n += 1 444 # 445 # ylabel_str = "Breakdown of Coherence Traffic Normalized w.r.t. \\nthe Values on %d Processors" % norm_factor_value 446 # content = template % dict(svg_name = os.path.join(graph_dir, prot + '_stacked'), xtics_str = xtics_str, plot_str = plot_str, ylabel_str = ylabel_str, app_labels = app_labels, prot_labels = "") 447 # 448 # create_file(gp_stacked_name, content) 449 # 450 # # Creating the data file 451 # # Values are normalized by application, w.r.t. the number of requests for a given number of procs 452 # content = "#" 453 # for stacked_metric in stacked_metrics: 454 # content += stacked_metric 455 # content += ' ' + ' ' * (15 - len(stacked_metric)) 456 # content += "\n" 457 # for app in apps: 458 # if app != apps[0]: 459 # for i in range(0, len(stacked_metrics)): 460 # content += "%-15f" % 0.0 461 # content += "\n" 462 # for i in nb_procs[1:len(nb_procs)]: 463 # for stacked_metric in stacked_metrics: 464 # metric_val = metrics_val[prot][app][norm_factor_value]['total_stacked'] # Normalisation 465 # if metric_val != 0: 466 # content += "%-15f" % (float(metrics_val[prot][app][i][stacked_metric]) / metric_val) 467 # else: 468 # content += "%-15f" % 0 469 # content += "\n" 470 # 471 # create_file(data_stacked_name, content) 472 # # Calling gnuplot 473 # print "gnuplot", gp_stacked_name 474 # subprocess.call([ 'gnuplot', gp_stacked_name ]) 469 475 470 476 … … 508 514 xpos += 3 509 515 app_name_xpos = float((xpos_first + xpos_last)) / 2 510 app_labels += "set label \"%s\" at first %f,character 1 center font \"Times, 12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos)516 app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,28\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 511 517 #xpos += 1 512 518 xtics_str += ")" … … 518 524 n += 1 519 525 520 ylabel_str = "Coherence Cost Compared to Direct Requests Cost,\\nNormalized per Application for each Number of Processors"526 ylabel_str = "Coherence Cost Vs. Direct Requests Cost,\\nNormalized w.r.t. Direct Requests Cost" 521 527 content = template % dict(svg_name = os.path.join(graph_dir, prot + '_rel_cost'), xtics_str = xtics_str, plot_str = plot_str, ylabel_str = ylabel_str, app_labels = app_labels, prot_labels = "") 522 528 … … 581 587 582 588 583 for app in apps: 584 585 data_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_speedup.dat') 586 gp_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_speedup.gp') 587 588 # Creating data file 589 width = 15 590 content = "#nb_procs" 591 nb_spaces = width - len(content) 592 content += nb_spaces * ' ' 593 content += "speedup\n" 594 595 for i in nb_procs: 596 content += "%-15d " % i 597 for prot in joint_protocols: 598 val = exec_time[prot][app][i] 599 content += "%-15f " % (exec_time[joint_protocols[0]][app][1] / float(val)) 600 content += "\n" 601 602 create_file(data_speedup_name, content) 603 604 # Creating the gp file 605 template_file = open(speedup_tmpl, 'r') 606 template = template_file.read() 607 608 plot_str = "" 609 col = 2 610 for prot in joint_protocols: 611 if prot != joint_protocols[0]: 612 plot_str += ", \\\n " 613 plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_prot_name[prot] + "\" with linespoint" 614 col += 1 615 616 gp_commands = template % dict(appli = m_app_name[app] + " Normalized w.r.t. " + m_prot_name[joint_protocols[0]] + " on 1 Processor", nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, 'joint_' + app + '_speedup')) 617 618 create_file(gp_speedup_name, gp_commands) 619 620 # Calling gnuplot 621 print "gnuplot", gp_speedup_name 622 subprocess.call([ 'gnuplot', gp_speedup_name ]) 589 #if 1 in nb_procs: 590 # for app in apps: 591 # 592 # data_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_speedup.dat') 593 # gp_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_speedup.gp') 594 # 595 # # Creating data file 596 # width = 15 597 # content = "#nb_procs" 598 # nb_spaces = width - len(content) 599 # content += nb_spaces * ' ' 600 # content += "speedup\n" 601 # 602 # for i in nb_procs: 603 # content += "%-15d " % i 604 # for prot in joint_protocols: 605 # val = exec_time[prot][app][i] 606 # content += "%-15f " % (exec_time[joint_protocols[0]][app][1] / float(val)) 607 # content += "\n" 608 # 609 # create_file(data_speedup_name, content) 610 # 611 # # Creating the gp file 612 # template_file = open(speedup_tmpl, 'r') 613 # template = template_file.read() 614 # 615 # plot_str = "" 616 # col = 2 617 # for prot in joint_protocols: 618 # if prot != joint_protocols[0]: 619 # plot_str += ", \\\n " 620 # plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_prot_name[prot] + "\" with linespoint" 621 # col += 1 622 # 623 # gp_commands = template % dict(appli = m_app_name[app] + " Normalized w.r.t. " + m_prot_name[joint_protocols[0]] + " on 1 Processor", nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, 'joint_' + app + '_speedup')) 624 # 625 # create_file(gp_speedup_name, gp_commands) 626 # 627 # # Calling gnuplot 628 # print "gnuplot", gp_speedup_name 629 # subprocess.call([ 'gnuplot', gp_speedup_name ]) 623 630 624 631 … … 638 645 template_file = open(stacked_tmpl, 'r') 639 646 template = template_file.read() 640 647 641 648 xtics_str = "(" 642 649 first = True 643 xpos = 1 # successive x position of the center of the first bar in a application 650 barwidth = 1 651 xpos = 1 # successive x position of the center of the first bar in an application 644 652 app_labels = "" 645 653 prot_labels = "" … … 650 658 x = 0 # local var for computing position of protocol names 651 659 for prot in joint_protocols: 652 prot_labels += "set label \"%s\" at first %f, character 2 center font \"Times,10\" \n" % (m_prot_name[prot], float((xpos - 0.5)) + x) # -0.5 instead of +0.5, don't know why... (bug gnuplot?)660 prot_labels += "set label \"%s\" at first %f, character 2 center font \"Times,10\" rotate by 45\n" % (m_prot_name[prot], float((xpos - 0.5)) + x - 1) # -0.5 instead of +0.5, don't know why... (bug gnuplot?) 653 661 x += 2 654 662 … … 660 668 xpos_first = xpos 661 669 xtics_str += "\"%d\" %f -1" % (i, float(xpos - 0.5 + len(joint_protocols))) 670 #xtics_str += "\"\" %f -1" % (float(xpos - 0.5 + len(joint_protocols))) # not to have proc number displayed 662 671 xpos_last = xpos 663 xpos += 1 + len(joint_protocols) * 2 664 app_name_xpos = float((xpos_first + xpos_last)) / 2 672 xpos += 1 + len(joint_protocols) * 2 * barwidth 673 app_name_xpos = float((xpos_first + xpos_last)) / 2 + 2 665 674 app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos) 666 xpos += 1675 #xpos += 1 667 676 xtics_str += ")" 668 677 … … 673 682 n += 1 674 683 675 ylabel_str = "Coherence Cost andDirect Requests Cost,\\nNormalized per Application for each Number of Processors"684 ylabel_str = "Coherence Cost vs. Direct Requests Cost,\\nNormalized per Application for each Number of Processors" 676 685 content = template % dict(svg_name = os.path.join(graph_dir, 'joint_rel_cost'), xtics_str = xtics_str, plot_str = plot_str, ylabel_str = ylabel_str, app_labels = app_labels, prot_labels = prot_labels) 677 686 … … 800 809 801 810 802 803 811 ######################################################################################################### 812 ### Graph 10: Normalized exec times with no log scale: when scalability is achieved by constant time ### 813 ######################################################################################################### 814 815 816 if 1 in nb_procs: 817 for app in apps: 818 819 data_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_cst_exec_time.dat') 820 gp_speedup_name = os.path.join(scripts_path, gen_dir, 'joint_' + app + '_cst_exec_time.gp') 821 822 # Creating data file 823 width = 15 824 content = "#nb_procs" 825 nb_spaces = width - len(content) 826 content += nb_spaces * ' ' 827 content += "norm_exec_time\n" 828 829 for i in nb_procs: 830 content += "%-15d " % i 831 for prot in joint_protocols: 832 val = exec_time[prot][app][i] 833 content += "%-15f " % (float(val) / exec_time[joint_protocols[0]][app][1]) 834 content += "\n" 835 836 create_file(data_speedup_name, content) 837 838 # Creating the gp file 839 template_file = open(cst_exec_time_tmpl, 'r') 840 template = template_file.read() 841 842 plot_str = "" 843 col = 2 844 for prot in joint_protocols: 845 if prot != joint_protocols[0]: 846 plot_str += ", \\\n " 847 plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_prot_name[prot] + "\" with linespoint" 848 col += 1 849 850 gp_commands = template % dict(appli = m_app_name[app] + " Normalized w.r.t. " + m_prot_name[joint_protocols[0]] + " on 1 Processor", nb_procs = nb_procs[-1] + 1, plot_str = plot_str, svg_name = os.path.join(graph_dir, 'joint_' + app + '_cst_exec_time')) 851 852 create_file(gp_speedup_name, gp_commands) 853 854 # Calling gnuplot 855 print "gnuplot", gp_speedup_name 856 subprocess.call([ 'gnuplot', gp_speedup_name ]) 857 858 859
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