1*1b37a2a7SPierre Jolivet#!/usr/bin/env python3 2d3ae85c4SBarry Smith# 3a6cca095SBarry Smith# Computers speed up of Streams benchmark results generated by make streams and plots 4a6cca095SBarry Smith# 5a6cca095SBarry Smith# matplotlib can switch between different backends hence this needs to be run 6a6cca095SBarry Smith# twice to first generate a file and then display a window 7d3ae85c4SBarry Smith# 85b6bfdb9SJed Brownfrom __future__ import print_function 9d3ae85c4SBarry Smithimport os 10d3ae85c4SBarry Smith# 114198fb66SBarry Smithdef process(streamstype,fileoutput): 12d3ae85c4SBarry Smith import re 134198fb66SBarry Smith 14a6cca095SBarry Smith ff = open('scaling.log') 15d3ae85c4SBarry Smith data = ff.read() 16d3ae85c4SBarry Smith ff.close() 17d3ae85c4SBarry Smith 185e71baefSBarry Smith s = data.split('\n') 19d3ae85c4SBarry Smith triads = {} 20d3ae85c4SBarry Smith speedups = {} 214198fb66SBarry Smith size = 0 224198fb66SBarry Smith for i in s[0:-1]: 234198fb66SBarry Smith i = i.split() 244198fb66SBarry Smith triads[size] = float(i[1]) 254198fb66SBarry Smith size = size + 1 26d3ae85c4SBarry Smith 274198fb66SBarry Smith if size < 2: return 28293a2e3aSBarry Smith 29080f2f32SBarry Smith triads = list(triads.values()) 304198fb66SBarry Smith speedups = {} 314198fb66SBarry Smith for i in range(0,size): 324198fb66SBarry Smith speedups[i] = triads[i]/triads[0] 33d3ae85c4SBarry Smith 34d3ae85c4SBarry Smith try: 35d3ae85c4SBarry Smith import matplotlib 36d3ae85c4SBarry Smith except: 375b6bfdb9SJed Brown print("Unable to open matplotlib to plot speedup") 38d3ae85c4SBarry Smith return 39d3ae85c4SBarry Smith 40d3ae85c4SBarry Smith try: 41a6cca095SBarry Smith if fileoutput: matplotlib.use('Agg') 42d3ae85c4SBarry Smith import matplotlib.pyplot as plt 436a90b735SBarry Smith except: 445b6bfdb9SJed Brown print("Unable to open matplotlib to plot speedup") 456a90b735SBarry Smith return 46d3ae85c4SBarry Smith 47182d2d36SBarry Smith try: 487137e648SBarry Smith fig, ax1 = plt.subplots() 494198fb66SBarry Smith plt.title(streamstype+' Perfect and Streams Speedup') 507137e648SBarry Smith ax2 = ax1.twinx() 517137e648SBarry Smith ax1.set_autoscaley_on(False) 528473a99dSBarry Smith 534198fb66SBarry Smith r = range(1,size+1) 544198fb66SBarry Smith speedups = speedups.values() 554198fb66SBarry Smith 568473a99dSBarry Smith # make sure that actual bandwidth values (as opposed to perfect speedup) takes 578473a99dSBarry Smith # at least a third of the y axis 584198fb66SBarry Smith ymax = min(size, 3*max(speedups)) 594198fb66SBarry Smith ymin = min(1, min(speedups)) 604198fb66SBarry Smith if ymin < 1: ymin = 0 618473a99dSBarry Smith 624198fb66SBarry Smith ax1.set_xlim(1,size) 634198fb66SBarry Smith ax1.set_ylim([ymin,ymax]) 644198fb66SBarry Smith ax1.set_xlabel('Number of processes/threads') 657137e648SBarry Smith ax1.set_ylabel('Memory Bandwidth Speedup') 664198fb66SBarry Smith ax1.plot(r,r,'b',r,speedups,'r-o') 677137e648SBarry Smith ax2.set_autoscaley_on(False) 684198fb66SBarry Smith ax2.set_xlim([1,size]) 694198fb66SBarry Smith ax2.set_ylim([min(triads),max(triads)]) 704198fb66SBarry Smith ax2.set_ylabel("Achieved Bandwidth. Megabytes per Second") 714198fb66SBarry Smith ax2.plot(r,triads,'g-o') 727137e648SBarry Smith 73d3ae85c4SBarry Smith plt.show() 744198fb66SBarry Smith if fileoutput: plt.savefig(streamstype+'scaling.png') 754198fb66SBarry Smith if fileoutput: print("See graph in the file src/benchmarks/streams/"+streamstype+"scaling.png") 765b6bfdb9SJed Brown except Exception as e: 775b6bfdb9SJed Brown if fileoutput: print("Unable to plot speedup to a file") 785b6bfdb9SJed Brown else: print("Unable to display speedup plot") 79182d2d36SBarry Smith return 80d3ae85c4SBarry Smith 811df1832dSBarry Smith ff.close() 821df1832dSBarry Smith 83d3ae85c4SBarry Smith# 84d3ae85c4SBarry Smith# 85d3ae85c4SBarry Smithif __name__ == '__main__': 86d3ae85c4SBarry Smith import sys 874198fb66SBarry Smith 884198fb66SBarry Smith process(sys.argv[1],len(sys.argv)-2) 89d3ae85c4SBarry Smith 90d3ae85c4SBarry Smith 91