1#!/usr/bin/env python 2#!/bin/env python 3# 4# Computers speed up of Streams benchmark results generated by make streams and plots 5# 6# matplotlib can switch between different backends hence this needs to be run 7# twice to first generate a file and then display a window 8# 9from __future__ import print_function 10import os 11# 12def process(fileoutput = 1): 13 import re 14 ff = open('scaling.log') 15 data = ff.read() 16 ff.close() 17 18 s = data.split('\n') 19 ss = [] 20 for i in s: 21 if not i.startswith('MPI rank'): 22 ss.append(i) 23 data = '\n'.join(ss) 24 hosts = {} 25 triads = {} 26 speedups = {} 27 match = data.split('Number of MPI processes ') 28 for i in match: 29 if i: 30 fields = i.split('\n') 31 size = int(fields[0].split()[0]) 32 hosts[size] = fields[0].split()[3:] 33 triads[size] = float(fields[1].split()[1]) 34 35 if len(hosts) < 2: return 36 37 ff = open('scaling.log','a') 38 if fileoutput: print('np speedup') 39 if fileoutput: ff.write('np speedup\n') 40 for sizes in hosts: 41 speedups[sizes] = triads[sizes]/triads[1] 42 if fileoutput: print(sizes,round(triads[sizes]/triads[1],2)) 43 if fileoutput: ff.write(str(sizes)+' '+str(round(triads[sizes]/triads[1],2))+'\n') 44 45 if fileoutput: print("Estimation of possible speedup of MPI programs based on Streams benchmark.") 46 if fileoutput: ff.write("Estimation of possible speedup of MPI programs based on Streams benchmark.\n") 47 48 if fileoutput: 49 import re 50 last = max(hosts.keys()) 51 lasthosts = hosts[last] 52 for i in range(0,len(lasthosts)): 53 lasthosts[i] = re.sub(r"Process [0-9]*", "", lasthosts[i]) 54 ulasthosts = list(set(lasthosts)) 55 print("It appears you have "+str(len(ulasthosts))+" node(s)") 56 ff.write("It appears you have "+str(len(ulasthosts))+" node(s)\n") 57 58 if len(ulasthosts) < 1: 59 testhosts = [] 60 for i in range(0,len(lasthosts)): 61 testhosts.append(ulasthosts[i % len(ulasthosts)]) 62 if testhosts == lasthosts: 63 print(" distributed in a round robin order") 64 ff.write(" distributed in a round robin order\n") 65 else: 66 print(" NOT distributed in a round robin order") 67 ff.write(" NOT distributed in a round robin order\n") 68 69 try: 70 import matplotlib 71 except: 72 print("Unable to open matplotlib to plot speedup") 73 return 74 75 try: 76 if fileoutput: matplotlib.use('Agg') 77 import matplotlib.pyplot as plt 78 except: 79 print("Unable to open matplotlib to plot speedup") 80 return 81 82 try: 83 fig, ax1 = plt.subplots() 84 plt.title('MPI Perfect and Streams Speedup') 85 ax2 = ax1.twinx() 86 ax1.set_autoscaley_on(False) 87 88 # make sure that actual bandwidth values (as opposed to perfect speedup) takes 89 # at least a third of the y axis 90 ymax = min(max(hosts.keys()), 3*max(triads.values())/min(triads.values()) - 2) 91 92 ax1.set_xlim([min(hosts.keys()),max(hosts.keys())]) 93 ax1.set_ylim([min(hosts.keys()),ymax]) 94 ax1.set_xlabel('Number of MPI processes') 95 ax1.set_ylabel('Memory Bandwidth Speedup') 96 ax1.plot(hosts.keys(),hosts.keys(),'b',hosts.keys(),speedups.values(),'r-o') 97 ax2.set_autoscaley_on(False) 98 ax2.set_xlim([min(hosts.keys()),max(hosts.keys())]) 99 ax2.set_ylim([min(triads.values())/1000.,min(triads.values())*ymax/1000.]) 100 ax2.set_ylabel("Achieved Bandwidth. Gigabytes per Second") 101 102 plt.show() 103 if fileoutput: plt.savefig('scaling.png') 104 if fileoutput: print("See graph in the file src/benchmarks/streams/scaling.png") 105 if fileoutput: ff.write("See graph in the file src/benchmarks/streams/scaling.png\n") 106 except Exception as e: 107 if fileoutput: print("Unable to plot speedup to a file") 108 else: print("Unable to display speedup plot") 109 return 110 111 ff.close() 112 113# 114# 115if __name__ == '__main__': 116 import sys 117 process(len(sys.argv)-1) 118 119 120
