| 1 | #!/usr/bin/python
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| 2 |
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| 3 | import subprocess
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| 4 | import os
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| 5 | import re
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| 6 | import sys
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| 7 |
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| 8 |
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| 9 | #apps = [ 'histo-opt', 'mandel', 'filt_ga', 'radix_ga', 'fft_ga', 'pca-opt', 'fft', 'radix', 'filter', 'kmeans-opt' ]
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| 10 | apps = [ 'fft_ga', 'filt_ga', 'lu', 'radix_ga', 'histo-opt', 'mandel', 'pca-opt', 'kmeans-opt' ]
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| 11 | #apps = [ 'histogram', 'mandel', 'filter', 'fft', 'fft_ga', 'filt_ga', 'pca', 'lu' ] # radix radix_ga kmeans
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| 12 | #apps = [ 'histo-opt', 'histogram2', 'histo-opt2' ]
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| 13 | #nb_procs = [ 1, 4, 8, 16, 32, 64, 128, 256 ]
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| 14 | nb_procs = [ 1, 4, 8, 16, 32, 64, 128, 256 ]
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| 15 | single_protocols = ['dhccp', 'hmesi']
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| 16 | joint_protocols = ['dhccp', 'hmesi']
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| 17 | #joint_protocols = []
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| 18 |
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| 19 | top_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..")
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| 20 | scripts_path = os.path.join(top_path, 'scripts')
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| 21 | counter_defs_name = os.path.join(scripts_path, "counter_defs.py")
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| 22 |
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| 23 | exec(file(counter_defs_name))
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| 24 |
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| 25 | gen_dir = 'generated'
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| 26 | graph_dir = 'graph'
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| 27 | template_dir = 'templates'
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| 28 | data_dir = 'data'
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| 29 |
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| 30 | log_stdo_name = '_stdo_'
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| 31 | log_term_name = '_term_'
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| 32 |
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| 33 | coherence_tmpl = os.path.join(scripts_path, template_dir, 'coherence_template.gp') # 1 graph per appli
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| 34 | speedup_tmpl = os.path.join(scripts_path, template_dir, 'speedup_template.gp')
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| 35 | metric_tmpl = os.path.join(scripts_path, template_dir, 'metric_template.gp') # 1 graph per metric
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| 36 | stacked_tmpl = os.path.join(scripts_path, template_dir, 'stacked_template.gp')
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| 37 |
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| 38 |
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| 39 |
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| 40 | def create_file(name, content):
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| 41 | file = open(name, 'w')
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| 42 | file.write(content)
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| 43 | file.close()
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| 44 |
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| 45 | def is_numeric(s):
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| 46 | try:
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| 47 | float(s)
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| 48 | return True
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| 49 | except ValueError:
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| 50 | return False
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| 51 |
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| 52 | def get_x_y(nb_procs):
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| 53 | x = 1
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| 54 | y = 1
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| 55 | to_x = True
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| 56 | while (x * y * 4 < nb_procs):
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| 57 | if to_x:
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| 58 | x = x * 2
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| 59 | else:
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| 60 | y = y * 2
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| 61 | to_x = not to_x
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| 62 | return x, y
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| 63 |
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| 64 |
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| 65 |
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| 66 | # We first fill the m_metric_id table
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| 67 | for metric in all_metrics:
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| 68 | for tag in all_tags:
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| 69 | if m_metric_tag[metric] == tag:
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| 70 | m_metric_id[tag] = metric
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| 71 | break
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| 72 |
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| 73 |
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| 74 | # We start by processing all the log files
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| 75 | # Term files are processed for exec time only
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| 76 | # Init files are processed for all metrics
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| 77 | exec_time = {}
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| 78 | metrics_val = {}
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| 79 | for prot in joint_protocols:
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| 80 | metrics_val[prot] = {}
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| 81 | exec_time[prot] = {}
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| 82 | for app in apps:
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| 83 | exec_time[prot][app] = {}
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| 84 | metrics_val[prot][app] = {}
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| 85 | for i in nb_procs:
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| 86 | metrics_val[prot][app][i] = {}
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| 87 | log_stdo_file = os.path.join(scripts_path, data_dir, app + '_' + prot + log_stdo_name + str(i))
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| 88 | log_term_file = os.path.join(scripts_path, data_dir, app + '_' + prot + log_term_name + str(i))
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| 89 |
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| 90 | # Term
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| 91 | lines = open(log_term_file, 'r')
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| 92 | for line in lines:
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| 93 | tokens = line[:-1].split()
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| 94 | if len(tokens) > 0 and tokens[0] == "[PARALLEL_COMPUTE]":
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| 95 | exec_time[prot][app][i] = int(tokens[len(tokens) - 1])
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| 96 |
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| 97 | # Init files
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| 98 | lines = open(log_stdo_file, 'r')
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| 99 | for line in lines:
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| 100 | tokens = line[:-1].split()
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| 101 | if len(tokens) == 0:
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| 102 | continue
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| 103 | tag = tokens[0]
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| 104 | value = tokens[len(tokens) - 1]
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| 105 | pattern = re.compile('\[0[0-9][0-9]\]')
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| 106 | if pattern.match(tag):
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| 107 | metric = m_metric_id[tag]
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| 108 | if (not metrics_val[prot][app][i].has_key(metric) or tag == "[000]" or tag == "[001]"):
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| 109 | # We don't add cycles of all Memcaches (they must be the same for all)
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| 110 | metrics_val[prot][app][i][metric] = int(value)
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| 111 | else:
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| 112 | metrics_val[prot][app][i][metric] += int(value)
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| 113 |
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| 114 | # Completing unset metrics (i.e. they are not present in the data file) with 0
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| 115 | for prot in joint_protocols:
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| 116 | for app in apps:
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| 117 | for i in nb_procs:
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| 118 | for metric in all_metrics:
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| 119 | if metric not in metrics_val[prot][app][i]:
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| 120 | metrics_val[prot][app][i][metric] = 0
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| 121 |
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| 122 | # We make a 2nd pass to fill the derived fields, e.g. nb_total_updates
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| 123 | for prot in joint_protocols:
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| 124 | for app in apps:
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| 125 | for i in nb_procs:
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| 126 | x, y = get_x_y(i)
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| 127 | metrics_val[prot][app][i]['total_read'] = metrics_val[prot][app][i]['local_read'] + metrics_val[prot][app][i]['remote_read']
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| 128 | metrics_val[prot][app][i]['total_write'] = metrics_val[prot][app][i]['local_write'] + metrics_val[prot][app][i]['remote_write']
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| 129 | metrics_val[prot][app][i]['total_ll'] = metrics_val[prot][app][i]['local_ll'] + metrics_val[prot][app][i]['remote_ll']
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| 130 | metrics_val[prot][app][i]['total_sc'] = metrics_val[prot][app][i]['local_sc'] + metrics_val[prot][app][i]['remote_sc']
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| 131 | metrics_val[prot][app][i]['total_cas'] = metrics_val[prot][app][i]['local_cas'] + metrics_val[prot][app][i]['remote_cas']
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| 132 | metrics_val[prot][app][i]['total_update'] = metrics_val[prot][app][i]['local_update'] + metrics_val[prot][app][i]['remote_update']
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| 133 | metrics_val[prot][app][i]['total_m_inv'] = metrics_val[prot][app][i]['local_m_inv'] + metrics_val[prot][app][i]['remote_m_inv']
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| 134 | metrics_val[prot][app][i]['total_cleanup'] = metrics_val[prot][app][i]['local_cleanup'] + metrics_val[prot][app][i]['remote_cleanup']
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| 135 | metrics_val[prot][app][i]['total_cleanup_d'] = metrics_val[prot][app][i]['local_cleanup_d'] + metrics_val[prot][app][i]['remote_cleanup_d']
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| 136 | metrics_val[prot][app][i]['total_getm'] = metrics_val[prot][app][i]['local_getm'] + metrics_val[prot][app][i]['remote_getm']
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| 137 | metrics_val[prot][app][i]['total_inval_ro'] = metrics_val[prot][app][i]['local_inval_ro'] + metrics_val[prot][app][i]['remote_inval_ro']
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| 138 | metrics_val[prot][app][i]['total_direct'] = metrics_val[prot][app][i]['total_read'] + metrics_val[prot][app][i]['total_write']
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| 139 | metrics_val[prot][app][i]['total_ncc_to_cc'] = metrics_val[prot][app][i]['ncc_to_cc_read'] + metrics_val[prot][app][i]['ncc_to_cc_write']
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| 140 | metrics_val[prot][app][i]['direct_cost'] = metrics_val[prot][app][i]['read_cost'] + metrics_val[prot][app][i]['write_cost']
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| 141 | metrics_val[prot][app][i]['broadcast_cost'] = metrics_val[prot][app][i]['broadcast'] * 2 * (x * y - 1)
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| 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']
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| 143 | if metrics_val[prot][app][i]['broadcast'] < metrics_val[prot][app][i]['write_broadcast']:
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| 144 | # test to patch a bug in mem_cache
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| 145 | metrics_val[prot][app][i]['nonwrite_broadcast'] = 0
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| 146 | print "*** Error which should not happen anymore: incorrect number of Broadcasts/Write Broadcasts"
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| 147 | else:
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| 148 | metrics_val[prot][app][i]['nonwrite_broadcast'] = metrics_val[prot][app][i]['broadcast'] - metrics_val[prot][app][i]['write_broadcast']
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| 149 |
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| 150 | metrics_val[prot][app][i]['total_stacked'] = 0
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| 151 | for stacked_metric in stacked_metrics:
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| 152 | metrics_val[prot][app][i]['total_stacked'] += metrics_val[prot][app][i][stacked_metric]
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| 153 |
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| 154 |
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| 155 | print "mkdir -p", os.path.join(scripts_path, gen_dir)
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| 156 | subprocess.call([ 'mkdir', '-p', os.path.join(scripts_path, gen_dir) ])
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| 157 |
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| 158 | print "mkdir -p", os.path.join(scripts_path, graph_dir)
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| 159 | subprocess.call([ 'mkdir', '-p', os.path.join(scripts_path, graph_dir) ])
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| 160 |
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| 161 | ############################################################
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| 162 | ### Graph 1 : Coherence traffic Cost per application ###
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| 163 | ############################################################
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| 164 |
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| 165 | for prot in single_protocols:
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| 166 | for app in apps:
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| 167 | data_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.dat')
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| 168 | gp_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.gp')
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| 169 |
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| 170 | # Creating the data file
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| 171 | width = 15
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| 172 | content = ""
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| 173 |
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| 174 | for metric in [ '#nb_procs' ] + grouped_metrics:
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| 175 | content += metric + " "
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| 176 | nb_spaces = width - len(metric)
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| 177 | content += nb_spaces * ' '
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| 178 | content += "\n"
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| 179 |
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| 180 | for i in nb_procs:
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| 181 | content += "%-15d " % i
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| 182 | for metric in grouped_metrics:
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| 183 | val = float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000
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| 184 | content += "%-15f " % val
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| 185 | content += "\n"
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| 186 |
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| 187 | create_file(data_coherence_name, content)
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| 188 |
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| 189 | # Creating the gp file
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| 190 | template_file = open(coherence_tmpl, 'r')
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| 191 | template = template_file.read()
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| 192 |
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| 193 | plot_str = ""
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| 194 | col = 2
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| 195 | for metric in grouped_metrics:
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| 196 | if metric != grouped_metrics[0]:
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| 197 | plot_str += ", \\\n "
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| 198 | plot_str += "\"" + data_coherence_name + "\" using ($1):($" + str(col) + ") lc rgb " + colors[col - 2] + " title \"" + m_metric_name[metric] + "\" with linespoint"
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| 199 | col += 1
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| 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'))
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| 201 |
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| 202 | create_file(gp_coherence_name, gp_commands)
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| 203 |
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| 204 | # Calling gnuplot
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| 205 | print "gnuplot", gp_coherence_name
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| 206 | subprocess.call([ 'gnuplot', gp_coherence_name ])
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| 207 |
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| 208 |
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| 209 | ############################################################
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| 210 | ### Graph 2 : Speedup per Application ###
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| 211 | ############################################################
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| 212 |
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| 213 | for prot in single_protocols:
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| 214 | for app in apps:
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| 215 |
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| 216 | data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.dat')
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| 217 | gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.gp')
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| 218 |
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| 219 | # Creating data file
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| 220 | width = 15
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| 221 | content = "#nb_procs"
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| 222 | nb_spaces = width - len(content)
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| 223 | content += nb_spaces * ' '
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| 224 | content += "speedup\n"
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| 225 |
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| 226 | for i in nb_procs:
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| 227 | content += "%-15d " % i
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| 228 | val = exec_time[prot][app][i]
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| 229 | content += "%-15f\n" % (exec_time[prot][app][1] / float(val))
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| 230 |
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| 231 | plot_str = "\"" + data_speedup_name + "\" using ($1):($2) lc rgb \"#654387\" title \"Speedup\" with linespoint"
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| 232 |
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| 233 | create_file(data_speedup_name, content)
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| 234 |
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| 235 | # Creating the gp file
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| 236 | template_file = open(speedup_tmpl, 'r')
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| 237 | template = template_file.read()
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| 238 |
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| 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'))
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| 240 |
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| 241 | create_file(gp_speedup_name, gp_commands)
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| 242 |
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| 243 | # Calling gnuplot
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| 244 | print "gnuplot", gp_speedup_name
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| 245 | subprocess.call([ 'gnuplot', gp_speedup_name ])
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| 246 |
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| 247 |
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| 248 | ############################################################
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| 249 | ### Graph 3 : All speedups on the same Graph ###
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| 250 | ############################################################
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| 251 |
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| 252 | for prot in single_protocols:
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| 253 | # This graph uses the same template as the graph 2
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| 254 | data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.dat')
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| 255 | gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.gp')
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| 256 |
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| 257 | # Creating data file
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| 258 | width = 15
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| 259 | content = "#nb_procs"
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| 260 | nb_spaces = width - len(content)
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| 261 | content += (nb_spaces + 1) * ' '
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| 262 | for app in apps:
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| 263 | content += app + " "
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| 264 | content += (width - len(app)) * " "
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| 265 | content += "\n"
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| 266 |
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| 267 | for i in nb_procs:
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| 268 | content += "%-15d " % i
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| 269 | for app in apps:
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| 270 | val = exec_time[prot][app][i]
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| 271 | content += "%-15f " % (exec_time[prot][app][1] / float(val))
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| 272 | content += "\n"
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| 273 |
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| 274 | create_file(data_speedup_name, content)
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| 275 |
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| 276 | # Creating gp file
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| 277 | template_file = open(speedup_tmpl, 'r')
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| 278 | template = template_file.read()
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| 279 |
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| 280 | plot_str = ""
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| 281 | col = 2
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| 282 | for app in apps:
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| 283 | if app != apps[0]:
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| 284 | plot_str += ", \\\n "
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| 285 | plot_str += "\"" + data_speedup_name + "\" using ($1):($" + str(col) + ") lc rgb %s title \"" % (colors[col - 2]) + m_app_name[app] + "\" with linespoint"
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| 286 | col += 1
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| 287 |
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| 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'))
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| 289 |
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| 290 | create_file(gp_speedup_name, gp_commands)
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| 291 |
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| 292 | # Calling gnuplot
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| 293 | print "gnuplot", gp_speedup_name
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| 294 | subprocess.call([ 'gnuplot', gp_speedup_name ])
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| 295 |
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| 296 |
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| 297 | ############################################################
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| 298 | ### Graph 4 : Graph per metric ###
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| 299 | ############################################################
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| 300 |
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| 301 | # The following section creates the graphs grouped by measure (e.g. #broadcasts)
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| 302 | # The template file cannot be easily created otherwise it would not be generic
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| 303 | # in many ways. This is why it is mainly created here.
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| 304 | # Graphs are created for metric in the "individual_metrics" list
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| 305 |
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| 306 | for prot in single_protocols:
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| 307 | for metric in individual_metrics:
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| 308 | data_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.dat')
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| 309 | gp_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.gp')
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| 310 |
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| 311 | # Creating the gp file
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| 312 | # Setting xtics, i.e. number of procs for each application
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| 313 | xtics_str = "("
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| 314 | first = True
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| 315 | xpos = 1
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| 316 | app_labels = ""
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| 317 | for num_appli in range(0, len(apps)):
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| 318 | for i in nb_procs:
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| 319 | if not first:
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| 320 | xtics_str += ", "
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| 321 | first = False
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| 322 | if i == nb_procs[0]:
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| 323 | xpos_first = xpos
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| 324 | xtics_str += "\"%d\" %.1f" % (i, xpos)
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| 325 | xpos_last = xpos
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| 326 | xpos += 1.5
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| 327 | xpos += 0.5
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| 328 | app_name_xpos = float((xpos_first + xpos_last)) / 2
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| 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)
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| 330 | xtics_str += ")"
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| 331 |
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| 332 | xmax_val = float(xpos - 1)
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| 333 |
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| 334 | # Writing the lines of "plot"
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| 335 | plot_str = ""
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| 336 | xpos = 0
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| 337 | first = True
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| 338 | column = 2
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| 339 | for i in range(0, len(nb_procs)):
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| 340 | if not first:
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| 341 | plot_str += ", \\\n "
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|---|
| 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 ])
|
|---|
| 469 |
|
|---|
| 470 |
|
|---|
| 471 |
|
|---|
| 472 | #################################################################################
|
|---|
| 473 | ### Graph 6 : Stacked histogram with coherence cost compared to r/w cost ###
|
|---|
| 474 | #################################################################################
|
|---|
| 475 |
|
|---|
| 476 | # The following section creates pairs of stacked histograms, normalized w.r.t. the first one.
|
|---|
| 477 | # The first one contains the cost of reads and writes, the second contains the cost
|
|---|
| 478 | # of m_inv, m_up and broadcasts (extrapolated)
|
|---|
| 479 |
|
|---|
| 480 | for prot in single_protocols:
|
|---|
| 481 | data_cost_filename = os.path.join(scripts_path, gen_dir, prot + '_relative_cost.dat')
|
|---|
| 482 | gp_cost_filename = os.path.join(scripts_path, gen_dir, prot + '_relative_cost.gp')
|
|---|
| 483 |
|
|---|
| 484 | direct_cost_metrics = [ 'read_cost', 'write_cost' ]
|
|---|
| 485 | #coherence_cost_metrics = ['update_cost', 'm_inv_cost', 'broadcast_cost' ]
|
|---|
| 486 | coherence_cost_metrics = ['coherence_cost']
|
|---|
| 487 |
|
|---|
| 488 | # Creating the gp file
|
|---|
| 489 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 490 | template = template_file.read()
|
|---|
| 491 |
|
|---|
| 492 | xtics_str = "("
|
|---|
| 493 | first = True
|
|---|
| 494 | xpos = 1
|
|---|
| 495 | app_labels = ""
|
|---|
| 496 | for num_appli in range(0, len(apps)):
|
|---|
| 497 | first_proc = True
|
|---|
| 498 | for i in nb_procs:
|
|---|
| 499 | if i > 4:
|
|---|
| 500 | if not first:
|
|---|
| 501 | xtics_str += ", "
|
|---|
| 502 | first = False
|
|---|
| 503 | if first_proc:
|
|---|
| 504 | first_proc = False
|
|---|
| 505 | xpos_first = xpos
|
|---|
| 506 | xtics_str += "\"%d\" %f -1" % (i, float(xpos + 0.5))
|
|---|
| 507 | xpos_last = xpos
|
|---|
| 508 | xpos += 3
|
|---|
| 509 | 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)
|
|---|
| 511 | #xpos += 1
|
|---|
| 512 | xtics_str += ")"
|
|---|
| 513 |
|
|---|
| 514 | plot_str = "newhistogram \"\""
|
|---|
| 515 | n = 1
|
|---|
| 516 | for cost_metric in direct_cost_metrics + coherence_cost_metrics:
|
|---|
| 517 | plot_str += ", \\\n " + "'" + data_cost_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[cost_metric] + "\""
|
|---|
| 518 | n += 1
|
|---|
| 519 |
|
|---|
| 520 | ylabel_str = "Coherence Cost Compared to Direct Requests Cost,\\nNormalized per Application for each Number of Processors"
|
|---|
| 521 | 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 |
|
|---|
| 523 | create_file(gp_cost_filename, content)
|
|---|
| 524 |
|
|---|
| 525 | # Creating the data file
|
|---|
| 526 | # Values are normalized by application, w.r.t. the number of requests for a given number of procs
|
|---|
| 527 | content = "#"
|
|---|
| 528 | for cost_metric in direct_cost_metrics:
|
|---|
| 529 | content += cost_metric
|
|---|
| 530 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 531 | for cost_metric in coherence_cost_metrics:
|
|---|
| 532 | content += cost_metric
|
|---|
| 533 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 534 | content += "\n"
|
|---|
| 535 | for app in apps:
|
|---|
| 536 | if app != apps[0]:
|
|---|
| 537 | for i in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 538 | content += "%-15f" % 0.0
|
|---|
| 539 | content += "\n"
|
|---|
| 540 | for i in nb_procs:
|
|---|
| 541 | if i > 4:
|
|---|
| 542 | for cost_metric in direct_cost_metrics:
|
|---|
| 543 | if metrics_val[prot][app][i]['direct_cost'] == 0:
|
|---|
| 544 | print "Error: prot : ", prot, " - app : ", app, " - i : ", i
|
|---|
| 545 | content += "%-15f" % 0
|
|---|
| 546 | else:
|
|---|
| 547 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[prot][app][i]['direct_cost'])
|
|---|
| 548 | for cost_metric in coherence_cost_metrics:
|
|---|
| 549 | content += "%-15f" % 0.0
|
|---|
| 550 | content += "\n"
|
|---|
| 551 | for cost_metric in direct_cost_metrics:
|
|---|
| 552 | content += "%-15f" % 0.0
|
|---|
| 553 | for cost_metric in coherence_cost_metrics:
|
|---|
| 554 | if metrics_val[prot][app][i]['direct_cost'] == 0:
|
|---|
| 555 | print "Error: prot : ", prot, " - app : ", app, " - i : ", i
|
|---|
| 556 | content += "%-15f" % 0
|
|---|
| 557 | else:
|
|---|
| 558 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[prot][app][i]['direct_cost'])
|
|---|
| 559 | content += "\n"
|
|---|
| 560 | if i != nb_procs[-1]:
|
|---|
| 561 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 562 | content += "%-15f" % 0.0
|
|---|
| 563 | content += "\n"
|
|---|
| 564 |
|
|---|
| 565 | create_file(data_cost_filename, content)
|
|---|
| 566 | # Calling gnuplot
|
|---|
| 567 | print "gnuplot", gp_cost_filename
|
|---|
| 568 | subprocess.call([ 'gnuplot', gp_cost_filename ])
|
|---|
| 569 |
|
|---|
| 570 |
|
|---|
| 571 | #################################################################################
|
|---|
| 572 | ### Joint Graphs to several architectures ###
|
|---|
| 573 | #################################################################################
|
|---|
| 574 |
|
|---|
| 575 | if len(joint_protocols) == 0:
|
|---|
| 576 | sys.exit()
|
|---|
| 577 |
|
|---|
| 578 | #################################################################################
|
|---|
| 579 | ### Graph 7: Comparison of Speedups (normalized w.r.t. 1 proc on first arch) ###
|
|---|
| 580 | #################################################################################
|
|---|
| 581 |
|
|---|
| 582 |
|
|---|
| 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 ])
|
|---|
| 623 |
|
|---|
| 624 |
|
|---|
| 625 | #################################################################################
|
|---|
| 626 | ### Graph 8 : Joint Stacked histogram with coherence cost and r/w cost ###
|
|---|
| 627 | #################################################################################
|
|---|
| 628 |
|
|---|
| 629 | # The following section creates pairs of stacked histograms for each arch for each number of proc for each app, normalized by (app x number of procs) (with first arch, R/W cost, first of the 2*num_arch histo). It is close to Graph 6
|
|---|
| 630 |
|
|---|
| 631 | data_cost_filename = os.path.join(scripts_path, gen_dir, 'joint_relative_cost.dat')
|
|---|
| 632 | gp_cost_filename = os.path.join(scripts_path, gen_dir, 'joint_relative_cost.gp')
|
|---|
| 633 |
|
|---|
| 634 | direct_cost_metrics = [ 'read_cost', 'write_cost', 'getm_cost' ]
|
|---|
| 635 | coherence_cost_metrics = ['update_cost', 'm_inv_cost', 'broadcast_cost', 'inval_ro_cost', 'cleanup_cost', 'cleanup_d_cost' ]
|
|---|
| 636 |
|
|---|
| 637 | # Creating the gp file
|
|---|
| 638 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 639 | template = template_file.read()
|
|---|
| 640 |
|
|---|
| 641 | xtics_str = "("
|
|---|
| 642 | first = True
|
|---|
| 643 | xpos = 1 # successive x position of the center of the first bar in a application
|
|---|
| 644 | app_labels = ""
|
|---|
| 645 | prot_labels = ""
|
|---|
| 646 | for num_appli in range(0, len(apps)):
|
|---|
| 647 | first_proc = True
|
|---|
| 648 | for i in nb_procs:
|
|---|
| 649 | if i > 4:
|
|---|
| 650 | x = 0 # local var for computing position of protocol names
|
|---|
| 651 | 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?)
|
|---|
| 653 | x += 2
|
|---|
| 654 |
|
|---|
| 655 | if not first:
|
|---|
| 656 | xtics_str += ", "
|
|---|
| 657 | first = False
|
|---|
| 658 | if first_proc:
|
|---|
| 659 | first_proc = False
|
|---|
| 660 | xpos_first = xpos
|
|---|
| 661 | xtics_str += "\"%d\" %f -1" % (i, float(xpos - 0.5 + len(joint_protocols)))
|
|---|
| 662 | xpos_last = xpos
|
|---|
| 663 | xpos += 1 + len(joint_protocols) * 2
|
|---|
| 664 | app_name_xpos = float((xpos_first + xpos_last)) / 2
|
|---|
| 665 | 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 += 1
|
|---|
| 667 | xtics_str += ")"
|
|---|
| 668 |
|
|---|
| 669 | plot_str = "newhistogram \"\""
|
|---|
| 670 | n = 1
|
|---|
| 671 | for cost_metric in direct_cost_metrics + coherence_cost_metrics:
|
|---|
| 672 | plot_str += ", \\\n " + "'" + data_cost_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[cost_metric] + "\""
|
|---|
| 673 | n += 1
|
|---|
| 674 |
|
|---|
| 675 | ylabel_str = "Coherence Cost and Direct Requests Cost,\\nNormalized per Application for each Number of Processors"
|
|---|
| 676 | 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 |
|
|---|
| 678 | create_file(gp_cost_filename, content)
|
|---|
| 679 |
|
|---|
| 680 | # Creating the data file
|
|---|
| 681 | # Values are normalized by application, w.r.t. the number of requests for a given number of procs
|
|---|
| 682 | content = "#"
|
|---|
| 683 | for cost_metric in direct_cost_metrics:
|
|---|
| 684 | content += cost_metric
|
|---|
| 685 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 686 | for cost_metric in coherence_cost_metrics:
|
|---|
| 687 | content += cost_metric
|
|---|
| 688 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 689 | content += "\n"
|
|---|
| 690 | for app in apps:
|
|---|
| 691 | if app != apps[0]:
|
|---|
| 692 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 693 | content += "%-15f" % 0.0
|
|---|
| 694 | content += "\n"
|
|---|
| 695 | for i in nb_procs:
|
|---|
| 696 | if i > 4:
|
|---|
| 697 | for prot in joint_protocols:
|
|---|
| 698 | if metrics_val[joint_protocols[0]][app][i]['direct_cost'] == 0:
|
|---|
| 699 | continue
|
|---|
| 700 | for cost_metric in direct_cost_metrics:
|
|---|
| 701 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[joint_protocols[0]][app][i]['direct_cost'])
|
|---|
| 702 | for cost_metric in coherence_cost_metrics:
|
|---|
| 703 | content += "%-15f" % 0.0
|
|---|
| 704 | content += "\n"
|
|---|
| 705 | for cost_metric in direct_cost_metrics:
|
|---|
| 706 | content += "%-15f" % 0.0
|
|---|
| 707 | for cost_metric in coherence_cost_metrics:
|
|---|
| 708 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[joint_protocols[0]][app][i]['direct_cost'])
|
|---|
| 709 | content += "\n"
|
|---|
| 710 | if i != nb_procs[-1]:
|
|---|
| 711 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 712 | content += "%-15f" % 0.0
|
|---|
| 713 | content += "\n"
|
|---|
| 714 |
|
|---|
| 715 | create_file(data_cost_filename, content)
|
|---|
| 716 | # Calling gnuplot
|
|---|
| 717 | print "gnuplot", gp_cost_filename
|
|---|
| 718 | subprocess.call([ 'gnuplot', gp_cost_filename ])
|
|---|
| 719 |
|
|---|
| 720 |
|
|---|
| 721 |
|
|---|
| 722 | #################################################################################
|
|---|
| 723 | ### Graph 9 : ###
|
|---|
| 724 | #################################################################################
|
|---|
| 725 |
|
|---|
| 726 |
|
|---|
| 727 | data_metric_filename = os.path.join(scripts_path, gen_dir, 'single_metric.dat')
|
|---|
| 728 | gp_metric_filename = os.path.join(scripts_path, gen_dir, 'single_metric.gp')
|
|---|
| 729 |
|
|---|
| 730 | metric = 'total_write'
|
|---|
| 731 |
|
|---|
| 732 | # Creating the gp file
|
|---|
| 733 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 734 | template = template_file.read()
|
|---|
| 735 |
|
|---|
| 736 | xtics_str = "("
|
|---|
| 737 | first = True
|
|---|
| 738 | xpos = 0 # successive x position of the center of the first bar in a application
|
|---|
| 739 | app_labels = ""
|
|---|
| 740 | prot_labels = ""
|
|---|
| 741 | for num_appli in range(0, len(apps)):
|
|---|
| 742 | first_proc = True
|
|---|
| 743 | for i in nb_procs:
|
|---|
| 744 | x = 0 # local var for computing position of protocol names
|
|---|
| 745 | #for prot in joint_protocols:
|
|---|
| 746 | #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?)
|
|---|
| 747 | #x += 1
|
|---|
| 748 |
|
|---|
| 749 | if not first:
|
|---|
| 750 | xtics_str += ", "
|
|---|
| 751 | first = False
|
|---|
| 752 | if first_proc:
|
|---|
| 753 | first_proc = False
|
|---|
| 754 | xpos_first = xpos
|
|---|
| 755 | xtics_str += "\"%d\" %f -1" % (i, float(xpos - 0.5 + len(joint_protocols)))
|
|---|
| 756 | xpos_last = xpos
|
|---|
| 757 | xpos += 1 + len(joint_protocols)
|
|---|
| 758 | app_name_xpos = float((xpos_first + xpos_last)) / 2
|
|---|
| 759 | app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos)
|
|---|
| 760 | xpos += 1
|
|---|
| 761 | xtics_str += ")"
|
|---|
| 762 |
|
|---|
| 763 | n = 1
|
|---|
| 764 | plot_str = "newhistogram \"\""
|
|---|
| 765 | for prot in joint_protocols:
|
|---|
| 766 | plot_str += ", \\\n " + "'" + data_metric_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[metric] + " for " + m_prot_name[prot] + "\""
|
|---|
| 767 | n += 1
|
|---|
| 768 |
|
|---|
| 769 | ylabel_str = "%(m)s" % dict(m = m_metric_name[metric])
|
|---|
| 770 | content = template % dict(svg_name = os.path.join(graph_dir, 'single_metric'), xtics_str = xtics_str, plot_str = plot_str, ylabel_str = ylabel_str, app_labels = app_labels, prot_labels = prot_labels)
|
|---|
| 771 |
|
|---|
| 772 | create_file(gp_metric_filename, content)
|
|---|
| 773 |
|
|---|
| 774 | # Creating the data file
|
|---|
| 775 | content = "#" + metric
|
|---|
| 776 | content += "\n"
|
|---|
| 777 | for app in apps:
|
|---|
| 778 | if app != apps[0]:
|
|---|
| 779 | for prot in joint_protocols:
|
|---|
| 780 | for p in joint_protocols:
|
|---|
| 781 | content += "%-15f " % 0.0
|
|---|
| 782 | content += "\n"
|
|---|
| 783 | for i in nb_procs:
|
|---|
| 784 | for prot in joint_protocols:
|
|---|
| 785 | for p in joint_protocols:
|
|---|
| 786 | if p != prot:
|
|---|
| 787 | content += "%-15f " % 0
|
|---|
| 788 | else:
|
|---|
| 789 | content += "%-15f " % (float(metrics_val[prot][app][i][metric]))
|
|---|
| 790 | content += "\n"
|
|---|
| 791 | if i != nb_procs[-1]:
|
|---|
| 792 | for p in joint_protocols:
|
|---|
| 793 | content += "%-15f " % 0.0
|
|---|
| 794 | content += "\n"
|
|---|
| 795 |
|
|---|
| 796 | create_file(data_metric_filename, content)
|
|---|
| 797 | # Calling gnuplot
|
|---|
| 798 | print "gnuplot", gp_metric_filename
|
|---|
| 799 | subprocess.call([ 'gnuplot', gp_metric_filename ])
|
|---|
| 800 |
|
|---|
| 801 |
|
|---|
| 802 |
|
|---|
| 803 |
|
|---|
