| 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 = [ 'blackscholes', 'filt_ga', 'fft_ga', 'histo-opt', 'kmeans-opt', 'linear_regression', 'lu', 'mandel', 'pca-opt', 'radix_ga', 'string_match' ]
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| 10 | #apps = [ 'blackscholes', 'fft_ga', 'filt_ga', 'histo-opt', 'kmeans-opt', 'linear_regression', 'lu', 'mandel', 'pca-opt', 'radix_ga' ]
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| 11 | #apps = [ 'histo-opt', 'mandel', 'filt_ga', 'radix_ga', 'fft_ga', 'pca-opt', 'fft', 'radix', 'filter', 'kmeans-opt' ]
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| 12 | #apps = [ 'histogram', 'mandel', 'filter', 'fft', 'fft_ga', 'filt_ga', 'pca', 'lu' ] # radix radix_ga kmeans
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| 13 | #apps = [ 'fal_sh_2' ]
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| 14 | nb_procs = [ 1, 4, 8, 16, 32, 64, 128, 256 ]
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| 15 | #nb_procs = [ 256 ]
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| 16 | single_protocols = ['dhccp', 'th0', 'hmesi', 'wtidl']
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| 17 | joint_protocols = ['dhccp', 'th0', 'hmesi', 'wtidl' ]
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| 18 | #joint_protocols = []
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| 19 |
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| 20 | top_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..")
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| 21 | scripts_path = os.path.join(top_path, 'scripts')
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| 22 | counter_defs_name = os.path.join(scripts_path, "counter_defs.py")
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| 23 |
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| 24 | exec(file(counter_defs_name))
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| 25 |
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| 26 | gen_dir = 'generated'
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| 27 | graph_dir = 'graph'
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| 28 | template_dir = 'templates'
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| 29 | data_dir = 'data'
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| 30 |
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| 31 | log_stdo_name = '_stdo_'
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| 32 | log_term_name = '_term_'
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| 33 |
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| 34 | coherence_tmpl = os.path.join(scripts_path, template_dir, 'coherence_template.gp') # 1 graph per appli
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| 35 | speedup_tmpl = os.path.join(scripts_path, template_dir, 'speedup_template.gp')
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| 36 | metric_tmpl = os.path.join(scripts_path, template_dir, 'metric_template.gp') # 1 graph per metric
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| 37 | stacked_tmpl = os.path.join(scripts_path, template_dir, 'stacked_template.gp')
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| 38 | cst_exec_time_tmpl = os.path.join(scripts_path, template_dir, 'cst_exec_time_template.gp')
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| 39 |
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| 40 |
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| 41 |
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| 42 | def create_file(name, content):
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| 43 | file = open(name, 'w')
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| 44 | file.write(content)
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| 45 | file.close()
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| 46 |
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| 47 | def is_numeric(s):
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| 48 | try:
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| 49 | float(s)
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| 50 | return True
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| 51 | except ValueError:
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| 52 | return False
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| 53 |
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| 54 | def get_x_y(nb_procs):
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| 55 | x = 1
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| 56 | y = 1
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| 57 | to_x = True
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| 58 | while (x * y * 4 < nb_procs):
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| 59 | if to_x:
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| 60 | x = x * 2
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| 61 | else:
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| 62 | y = y * 2
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| 63 | to_x = not to_x
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| 64 | return x, y
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| 65 |
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| 66 |
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| 67 |
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| 68 | # We first fill the m_metric_id table
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| 69 | for metric in all_metrics:
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| 70 | for tag in all_tags:
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| 71 | if m_metric_tag[metric] == tag:
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| 72 | m_metric_id[tag] = metric
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| 73 | break
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| 74 |
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| 75 |
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| 76 | # We start by processing all the log files
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| 77 | # Term files are processed for exec time only
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| 78 | # Init files are processed for all metrics
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| 79 | exec_time = {}
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| 80 | metrics_val = {}
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| 81 | for prot in joint_protocols:
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| 82 | metrics_val[prot] = {}
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| 83 | exec_time[prot] = {}
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| 84 | for app in apps:
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| 85 | exec_time[prot][app] = {}
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| 86 | metrics_val[prot][app] = {}
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| 87 | for i in nb_procs:
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| 88 | metrics_val[prot][app][i] = {}
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| 89 | log_stdo_file = os.path.join(scripts_path, data_dir, app + '_' + prot + log_stdo_name + str(i))
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| 90 | log_term_file = os.path.join(scripts_path, data_dir, app + '_' + prot + log_term_name + str(i))
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| 91 |
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| 92 | # Term
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| 93 | lines = open(log_term_file, 'r')
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| 94 | for line in lines:
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| 95 | tokens = line[:-1].split()
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| 96 | if len(tokens) > 0 and tokens[0] == "[PARALLEL_COMPUTE]":
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| 97 | exec_time[prot][app][i] = int(tokens[len(tokens) - 1])
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| 98 |
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| 99 | # Init files
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| 100 | lines = open(log_stdo_file, 'r')
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| 101 | for line in lines:
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| 102 | tokens = line[:-1].split()
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| 103 | if len(tokens) == 0:
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| 104 | continue
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| 105 | tag = tokens[0]
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| 106 | value = tokens[len(tokens) - 1]
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| 107 | pattern = re.compile('\[0[0-9][0-9]\]')
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| 108 | if pattern.match(tag):
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| 109 | metric = m_metric_id[tag]
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| 110 | if (not metrics_val[prot][app][i].has_key(metric) or tag == "[000]" or tag == "[001]"):
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| 111 | # We don't add cycles of all Memcaches (they must be the same for all)
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| 112 | metrics_val[prot][app][i][metric] = int(value)
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| 113 | else:
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| 114 | metrics_val[prot][app][i][metric] += int(value)
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| 115 |
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| 116 | # Completing unset metrics (i.e. they are not present in the data file) with 0
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| 117 | for prot in joint_protocols:
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| 118 | for app in apps:
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| 119 | for i in nb_procs:
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| 120 | for metric in all_metrics:
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| 121 | if metric not in metrics_val[prot][app][i]:
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| 122 | metrics_val[prot][app][i][metric] = 0
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| 123 |
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| 124 | # We make a 2nd pass to fill the derived fields, e.g. nb_total_updates
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| 125 | for prot in joint_protocols:
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| 126 | for app in apps:
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| 127 | for i in nb_procs:
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| 128 | x, y = get_x_y(i)
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| 129 | 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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| 130 | 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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| 131 | 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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| 132 | 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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| 133 | 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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| 134 | 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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| 135 | 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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| 136 | 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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| 137 | 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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| 138 | 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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| 139 | 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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| 140 | 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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| 141 | 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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| 142 | 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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| 143 | metrics_val[prot][app][i]['broadcast_cost'] = metrics_val[prot][app][i]['broadcast'] * 2 * (x * y - 1)
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| 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']
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| 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']
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| 146 | if metrics_val[prot][app][i]['broadcast'] < metrics_val[prot][app][i]['write_broadcast']:
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| 147 | # test to patch a bug in mem_cache
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| 148 | metrics_val[prot][app][i]['nonwrite_broadcast'] = 0
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| 149 | print "*** Error which should not happen anymore: incorrect number of Broadcasts/Write Broadcasts"
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| 150 | else:
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| 151 | metrics_val[prot][app][i]['nonwrite_broadcast'] = metrics_val[prot][app][i]['broadcast'] - metrics_val[prot][app][i]['write_broadcast']
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| 152 |
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| 153 | metrics_val[prot][app][i]['total_stacked'] = 0
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| 154 | for stacked_metric in stacked_metrics:
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| 155 | metrics_val[prot][app][i]['total_stacked'] += metrics_val[prot][app][i][stacked_metric]
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| 156 |
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| 157 |
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| 158 | print "mkdir -p", os.path.join(scripts_path, gen_dir)
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| 159 | subprocess.call([ 'mkdir', '-p', os.path.join(scripts_path, gen_dir) ])
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| 160 |
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| 161 | print "mkdir -p", os.path.join(scripts_path, graph_dir)
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| 162 | subprocess.call([ 'mkdir', '-p', os.path.join(scripts_path, graph_dir) ])
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| 163 |
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| 164 | #############################################################
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| 165 | #### Graph 1 : Coherence traffic Cost per application ###
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| 166 | #############################################################
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| 167 | #
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| 168 | #for prot in single_protocols:
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| 169 | # for app in apps:
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| 170 | # data_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.dat')
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| 171 | # gp_coherence_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_coherence.gp')
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| 172 | #
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| 173 | # # Creating the data file
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| 174 | # width = 15
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| 175 | # content = ""
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| 176 | #
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| 177 | # for metric in [ '#nb_procs' ] + grouped_metrics:
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| 178 | # content += metric + " "
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| 179 | # nb_spaces = width - len(metric)
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| 180 | # content += nb_spaces * ' '
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| 181 | # content += "\n"
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| 182 | #
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| 183 | # for i in nb_procs:
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| 184 | # content += "%-15d " % i
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| 185 | # for metric in grouped_metrics:
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| 186 | # #print "app : %s - prot : %s - i : %d" % (app, prot, i)
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| 187 | # val = float(metrics_val[prot][app][i][metric]) / exec_time[prot][app][i] * 1000
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| 188 | # content += "%-15f " % val
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| 189 | # content += "\n"
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| 190 | #
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| 191 | # create_file(data_coherence_name, content)
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| 192 | #
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| 193 | # # Creating the gp file
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| 194 | # template_file = open(coherence_tmpl, 'r')
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| 195 | # template = template_file.read()
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| 196 | #
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| 197 | # plot_str = ""
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| 198 | # col = 2
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| 199 | # for metric in grouped_metrics:
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| 200 | # if metric != grouped_metrics[0]:
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| 201 | # plot_str += ", \\\n "
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| 202 | # 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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| 203 | # col += 1
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| 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'))
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| 205 | #
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| 206 | # create_file(gp_coherence_name, gp_commands)
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| 207 | #
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| 208 | # # Calling gnuplot
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| 209 | # print "gnuplot", gp_coherence_name
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| 210 | # subprocess.call([ 'gnuplot', gp_coherence_name ])
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| 211 | #
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| 212 | #
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| 213 | #############################################################
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| 214 | #### Graph 2 : Speedup per Application ###
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| 215 | #############################################################
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| 216 | #
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| 217 | #if 1 in nb_procs:
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| 218 | # for prot in single_protocols:
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| 219 | # for app in apps:
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| 220 | #
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| 221 | # data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.dat')
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| 222 | # gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_' + app + '_speedup.gp')
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| 223 | #
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| 224 | # # Creating data file
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| 225 | # width = 15
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| 226 | # content = "#nb_procs"
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| 227 | # nb_spaces = width - len(content)
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| 228 | # content += nb_spaces * ' '
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| 229 | # content += "speedup\n"
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| 230 | #
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| 231 | # for i in nb_procs:
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| 232 | # content += "%-15d " % i
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| 233 | # val = exec_time[prot][app][i]
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| 234 | # content += "%-15f\n" % (exec_time[prot][app][1] / float(val))
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| 235 | #
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| 236 | # plot_str = "\"" + data_speedup_name + "\" using ($1):($2) lc rgb \"#654387\" title \"Speedup\" with linespoint"
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| 237 | #
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| 238 | # create_file(data_speedup_name, content)
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| 239 | #
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| 240 | # # Creating the gp file
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| 241 | # template_file = open(speedup_tmpl, 'r')
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| 242 | # template = template_file.read()
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| 243 | #
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| 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'))
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| 245 | #
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| 246 | # create_file(gp_speedup_name, gp_commands)
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| 247 | #
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| 248 | # # Calling gnuplot
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| 249 | # print "gnuplot", gp_speedup_name
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| 250 | # subprocess.call([ 'gnuplot', gp_speedup_name ])
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| 251 | #
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| 252 | #
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| 253 | #############################################################
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| 254 | #### Graph 3 : All speedups on the same Graph ###
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| 255 | #############################################################
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| 256 | #
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| 257 | #if 1 in nb_procs:
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| 258 | # for prot in single_protocols:
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| 259 | # # This graph uses the same template as the graph 2
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| 260 | # data_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.dat')
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| 261 | # gp_speedup_name = os.path.join(scripts_path, gen_dir, prot + '_all_speedup.gp')
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| 262 | #
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| 263 | # # Creating data file
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| 264 | # width = 15
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| 265 | # content = "#nb_procs"
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| 266 | # nb_spaces = width - len(content)
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| 267 | # content += (nb_spaces + 1) * ' '
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| 268 | # for app in apps:
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| 269 | # content += app + " "
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| 270 | # content += (width - len(app)) * " "
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| 271 | # content += "\n"
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| 272 | #
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| 273 | # for i in nb_procs:
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| 274 | # content += "%-15d " % i
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| 275 | # for app in apps:
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| 276 | # val = exec_time[prot][app][i]
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| 277 | # content += "%-15f " % (exec_time[prot][app][1] / float(val))
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| 278 | # content += "\n"
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| 279 | #
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| 280 | # create_file(data_speedup_name, content)
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| 281 | #
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| 282 | # # Creating gp file
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| 283 | # template_file = open(speedup_tmpl, 'r')
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| 284 | # template = template_file.read()
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| 285 | #
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| 286 | # plot_str = ""
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| 287 | # col = 2
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| 288 | # for app in apps:
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| 289 | # if app != apps[0]:
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| 290 | # plot_str += ", \\\n "
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| 291 | # 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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| 292 | # col += 1
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| 293 | #
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| 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'))
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| 295 | #
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| 296 | # create_file(gp_speedup_name, gp_commands)
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| 297 | #
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| 298 | # # Calling gnuplot
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| 299 | # print "gnuplot", gp_speedup_name
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| 300 | # subprocess.call([ 'gnuplot', gp_speedup_name ])
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| 301 | #
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| 302 | #
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| 303 | #############################################################
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| 304 | #### Graph 4 : Graph per metric ###
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| 305 | #############################################################
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| 306 | #
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| 307 | ## The following section creates the graphs grouped by measure (e.g. #broadcasts)
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| 308 | ## The template file cannot be easily created otherwise it would not be generic
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| 309 | ## in many ways. This is why it is mainly created here.
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| 310 | ## Graphs are created for metric in the "individual_metrics" list
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| 311 | #
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| 312 | #for prot in single_protocols:
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| 313 | # for metric in individual_metrics:
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| 314 | # data_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.dat')
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| 315 | # gp_metric_name = os.path.join(scripts_path, gen_dir, prot + '_' + metric + '.gp')
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| 316 | #
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| 317 | # # Creating the gp file
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| 318 | # # Setting xtics, i.e. number of procs for each application
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| 319 | # xtics_str = "("
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| 320 | # first = True
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| 321 | # xpos = 1
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| 322 | # app_labels = ""
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| 323 | # for num_appli in range(0, len(apps)):
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| 324 | # for i in nb_procs:
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| 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 ])
|
|---|
| 475 |
|
|---|
| 476 |
|
|---|
| 477 |
|
|---|
| 478 | #################################################################################
|
|---|
| 479 | ### Graph 6 : Stacked histogram with coherence cost compared to r/w cost ###
|
|---|
| 480 | #################################################################################
|
|---|
| 481 |
|
|---|
| 482 | # The following section creates pairs of stacked histograms, normalized w.r.t. the first one.
|
|---|
| 483 | # The first one contains the cost of reads and writes, the second contains the cost
|
|---|
| 484 | # of m_inv, m_up and broadcasts (extrapolated)
|
|---|
| 485 |
|
|---|
| 486 | for prot in single_protocols:
|
|---|
| 487 | data_cost_filename = os.path.join(scripts_path, gen_dir, prot + '_relative_cost.dat')
|
|---|
| 488 | gp_cost_filename = os.path.join(scripts_path, gen_dir, prot + '_relative_cost.gp')
|
|---|
| 489 |
|
|---|
| 490 | direct_cost_metrics = [ 'read_cost', 'write_cost' ]
|
|---|
| 491 | #coherence_cost_metrics = ['update_cost', 'm_inv_cost', 'broadcast_cost' ]
|
|---|
| 492 | coherence_cost_metrics = ['coherence_cost']
|
|---|
| 493 |
|
|---|
| 494 | # Creating the gp file
|
|---|
| 495 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 496 | template = template_file.read()
|
|---|
| 497 |
|
|---|
| 498 | xtics_str = "("
|
|---|
| 499 | first = True
|
|---|
| 500 | xpos = 1
|
|---|
| 501 | app_labels = ""
|
|---|
| 502 | for num_appli in range(0, len(apps)):
|
|---|
| 503 | first_proc = True
|
|---|
| 504 | for i in nb_procs:
|
|---|
| 505 | if i > 4:
|
|---|
| 506 | if not first:
|
|---|
| 507 | xtics_str += ", "
|
|---|
| 508 | first = False
|
|---|
| 509 | if first_proc:
|
|---|
| 510 | first_proc = False
|
|---|
| 511 | xpos_first = xpos
|
|---|
| 512 | xtics_str += "\"%d\" %f -1" % (i, float(xpos + 0.5))
|
|---|
| 513 | xpos_last = xpos
|
|---|
| 514 | xpos += 3
|
|---|
| 515 | app_name_xpos = float((xpos_first + xpos_last)) / 2
|
|---|
| 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)
|
|---|
| 517 | #xpos += 1
|
|---|
| 518 | xtics_str += ")"
|
|---|
| 519 |
|
|---|
| 520 | plot_str = "newhistogram \"\""
|
|---|
| 521 | n = 1
|
|---|
| 522 | for cost_metric in direct_cost_metrics + coherence_cost_metrics:
|
|---|
| 523 | plot_str += ", \\\n " + "'" + data_cost_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[cost_metric] + "\""
|
|---|
| 524 | n += 1
|
|---|
| 525 |
|
|---|
| 526 | ylabel_str = "Coherence Cost Vs. Direct Requests Cost,\\nNormalized w.r.t. Direct Requests Cost"
|
|---|
| 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 = "")
|
|---|
| 528 |
|
|---|
| 529 | create_file(gp_cost_filename, content)
|
|---|
| 530 |
|
|---|
| 531 | # Creating the data file
|
|---|
| 532 | # Values are normalized by application, w.r.t. the number of requests for a given number of procs
|
|---|
| 533 | content = "#"
|
|---|
| 534 | for cost_metric in direct_cost_metrics:
|
|---|
| 535 | content += cost_metric
|
|---|
| 536 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 537 | for cost_metric in coherence_cost_metrics:
|
|---|
| 538 | content += cost_metric
|
|---|
| 539 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 540 | content += "\n"
|
|---|
| 541 | for app in apps:
|
|---|
| 542 | if app != apps[0]:
|
|---|
| 543 | for i in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 544 | content += "%-15f" % 0.0
|
|---|
| 545 | content += "\n"
|
|---|
| 546 | for i in nb_procs:
|
|---|
| 547 | if i > 4:
|
|---|
| 548 | for cost_metric in direct_cost_metrics:
|
|---|
| 549 | if metrics_val[prot][app][i]['direct_cost'] == 0:
|
|---|
| 550 | print "Error: prot : ", prot, " - app : ", app, " - i : ", i
|
|---|
| 551 | content += "%-15f" % 0
|
|---|
| 552 | else:
|
|---|
| 553 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[prot][app][i]['direct_cost'])
|
|---|
| 554 | for cost_metric in coherence_cost_metrics:
|
|---|
| 555 | content += "%-15f" % 0.0
|
|---|
| 556 | content += "\n"
|
|---|
| 557 | for cost_metric in direct_cost_metrics:
|
|---|
| 558 | content += "%-15f" % 0.0
|
|---|
| 559 | for cost_metric in coherence_cost_metrics:
|
|---|
| 560 | if metrics_val[prot][app][i]['direct_cost'] == 0:
|
|---|
| 561 | print "Error: prot : ", prot, " - app : ", app, " - i : ", i
|
|---|
| 562 | content += "%-15f" % 0
|
|---|
| 563 | else:
|
|---|
| 564 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[prot][app][i]['direct_cost'])
|
|---|
| 565 | content += "\n"
|
|---|
| 566 | if i != nb_procs[-1]:
|
|---|
| 567 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 568 | content += "%-15f" % 0.0
|
|---|
| 569 | content += "\n"
|
|---|
| 570 |
|
|---|
| 571 | create_file(data_cost_filename, content)
|
|---|
| 572 | # Calling gnuplot
|
|---|
| 573 | print "gnuplot", gp_cost_filename
|
|---|
| 574 | subprocess.call([ 'gnuplot', gp_cost_filename ])
|
|---|
| 575 |
|
|---|
| 576 |
|
|---|
| 577 | #################################################################################
|
|---|
| 578 | ### Joint Graphs to several architectures ###
|
|---|
| 579 | #################################################################################
|
|---|
| 580 |
|
|---|
| 581 | if len(joint_protocols) == 0:
|
|---|
| 582 | sys.exit()
|
|---|
| 583 |
|
|---|
| 584 | #################################################################################
|
|---|
| 585 | ### Graph 7: Comparison of Speedups (normalized w.r.t. 1 proc on first arch) ###
|
|---|
| 586 | #################################################################################
|
|---|
| 587 |
|
|---|
| 588 |
|
|---|
| 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 ])
|
|---|
| 630 |
|
|---|
| 631 |
|
|---|
| 632 | #################################################################################
|
|---|
| 633 | ### Graph 8 : Joint Stacked histogram with coherence cost and r/w cost ###
|
|---|
| 634 | #################################################################################
|
|---|
| 635 |
|
|---|
| 636 | # 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
|
|---|
| 637 |
|
|---|
| 638 | data_cost_filename = os.path.join(scripts_path, gen_dir, 'joint_relative_cost.dat')
|
|---|
| 639 | gp_cost_filename = os.path.join(scripts_path, gen_dir, 'joint_relative_cost.gp')
|
|---|
| 640 |
|
|---|
| 641 | direct_cost_metrics = [ 'read_cost', 'write_cost', 'getm_cost' ]
|
|---|
| 642 | coherence_cost_metrics = ['update_cost', 'm_inv_cost', 'broadcast_cost', 'inval_ro_cost', 'cleanup_cost', 'cleanup_d_cost' ]
|
|---|
| 643 |
|
|---|
| 644 | # Creating the gp file
|
|---|
| 645 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 646 | template = template_file.read()
|
|---|
| 647 |
|
|---|
| 648 | xtics_str = "("
|
|---|
| 649 | first = True
|
|---|
| 650 | barwidth = 1
|
|---|
| 651 | xpos = 1 # successive x position of the center of the first bar in an application
|
|---|
| 652 | app_labels = ""
|
|---|
| 653 | prot_labels = ""
|
|---|
| 654 | for num_appli in range(0, len(apps)):
|
|---|
| 655 | first_proc = True
|
|---|
| 656 | for i in nb_procs:
|
|---|
| 657 | if i > 4:
|
|---|
| 658 | x = 0 # local var for computing position of protocol names
|
|---|
| 659 | for prot in joint_protocols:
|
|---|
| 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?)
|
|---|
| 661 | x += 2
|
|---|
| 662 |
|
|---|
| 663 | if not first:
|
|---|
| 664 | xtics_str += ", "
|
|---|
| 665 | first = False
|
|---|
| 666 | if first_proc:
|
|---|
| 667 | first_proc = False
|
|---|
| 668 | xpos_first = xpos
|
|---|
| 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
|
|---|
| 671 | xpos_last = xpos
|
|---|
| 672 | xpos += 1 + len(joint_protocols) * 2 * barwidth
|
|---|
| 673 | app_name_xpos = float((xpos_first + xpos_last)) / 2 + 2
|
|---|
| 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)
|
|---|
| 675 | #xpos += 1
|
|---|
| 676 | xtics_str += ")"
|
|---|
| 677 |
|
|---|
| 678 | plot_str = "newhistogram \"\""
|
|---|
| 679 | n = 1
|
|---|
| 680 | for cost_metric in direct_cost_metrics + coherence_cost_metrics:
|
|---|
| 681 | plot_str += ", \\\n " + "'" + data_cost_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[cost_metric] + "\""
|
|---|
| 682 | n += 1
|
|---|
| 683 |
|
|---|
| 684 | ylabel_str = "Coherence Cost vs. Direct Requests Cost,\\nNormalized per Application for each Number of Processors"
|
|---|
| 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)
|
|---|
| 686 |
|
|---|
| 687 | create_file(gp_cost_filename, content)
|
|---|
| 688 |
|
|---|
| 689 | # Creating the data file
|
|---|
| 690 | # Values are normalized by application, w.r.t. the number of requests for a given number of procs
|
|---|
| 691 | content = "#"
|
|---|
| 692 | for cost_metric in direct_cost_metrics:
|
|---|
| 693 | content += cost_metric
|
|---|
| 694 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 695 | for cost_metric in coherence_cost_metrics:
|
|---|
| 696 | content += cost_metric
|
|---|
| 697 | content += ' ' + ' ' * (15 - len(cost_metric))
|
|---|
| 698 | content += "\n"
|
|---|
| 699 | for app in apps:
|
|---|
| 700 | if app != apps[0]:
|
|---|
| 701 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 702 | content += "%-15f" % 0.0
|
|---|
| 703 | content += "\n"
|
|---|
| 704 | for i in nb_procs:
|
|---|
| 705 | if i > 4:
|
|---|
| 706 | for prot in joint_protocols:
|
|---|
| 707 | if metrics_val[joint_protocols[0]][app][i]['direct_cost'] == 0:
|
|---|
| 708 | continue
|
|---|
| 709 | for cost_metric in direct_cost_metrics:
|
|---|
| 710 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[joint_protocols[0]][app][i]['direct_cost'])
|
|---|
| 711 | for cost_metric in coherence_cost_metrics:
|
|---|
| 712 | content += "%-15f" % 0.0
|
|---|
| 713 | content += "\n"
|
|---|
| 714 | for cost_metric in direct_cost_metrics:
|
|---|
| 715 | content += "%-15f" % 0.0
|
|---|
| 716 | for cost_metric in coherence_cost_metrics:
|
|---|
| 717 | content += "%-15f" % (float(metrics_val[prot][app][i][cost_metric]) / metrics_val[joint_protocols[0]][app][i]['direct_cost'])
|
|---|
| 718 | content += "\n"
|
|---|
| 719 | if i != nb_procs[-1]:
|
|---|
| 720 | for j in range(0, len(direct_cost_metrics) + len(coherence_cost_metrics)):
|
|---|
| 721 | content += "%-15f" % 0.0
|
|---|
| 722 | content += "\n"
|
|---|
| 723 |
|
|---|
| 724 | create_file(data_cost_filename, content)
|
|---|
| 725 | # Calling gnuplot
|
|---|
| 726 | print "gnuplot", gp_cost_filename
|
|---|
| 727 | subprocess.call([ 'gnuplot', gp_cost_filename ])
|
|---|
| 728 |
|
|---|
| 729 |
|
|---|
| 730 |
|
|---|
| 731 | #################################################################################
|
|---|
| 732 | ### Graph 9 : ###
|
|---|
| 733 | #################################################################################
|
|---|
| 734 |
|
|---|
| 735 |
|
|---|
| 736 | data_metric_filename = os.path.join(scripts_path, gen_dir, 'single_metric.dat')
|
|---|
| 737 | gp_metric_filename = os.path.join(scripts_path, gen_dir, 'single_metric.gp')
|
|---|
| 738 |
|
|---|
| 739 | metric = 'total_write'
|
|---|
| 740 |
|
|---|
| 741 | # Creating the gp file
|
|---|
| 742 | template_file = open(stacked_tmpl, 'r')
|
|---|
| 743 | template = template_file.read()
|
|---|
| 744 |
|
|---|
| 745 | xtics_str = "("
|
|---|
| 746 | first = True
|
|---|
| 747 | xpos = 0 # successive x position of the center of the first bar in a application
|
|---|
| 748 | app_labels = ""
|
|---|
| 749 | prot_labels = ""
|
|---|
| 750 | for num_appli in range(0, len(apps)):
|
|---|
| 751 | first_proc = True
|
|---|
| 752 | for i in nb_procs:
|
|---|
| 753 | x = 0 # local var for computing position of protocol names
|
|---|
| 754 | #for prot in joint_protocols:
|
|---|
| 755 | #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?)
|
|---|
| 756 | #x += 1
|
|---|
| 757 |
|
|---|
| 758 | if not first:
|
|---|
| 759 | xtics_str += ", "
|
|---|
| 760 | first = False
|
|---|
| 761 | if first_proc:
|
|---|
| 762 | first_proc = False
|
|---|
| 763 | xpos_first = xpos
|
|---|
| 764 | xtics_str += "\"%d\" %f -1" % (i, float(xpos - 0.5 + len(joint_protocols)))
|
|---|
| 765 | xpos_last = xpos
|
|---|
| 766 | xpos += 1 + len(joint_protocols)
|
|---|
| 767 | app_name_xpos = float((xpos_first + xpos_last)) / 2
|
|---|
| 768 | app_labels += "set label \"%s\" at first %f,character 1 center font \"Times,12\"\n" % (m_app_name[apps[num_appli]], app_name_xpos)
|
|---|
| 769 | xpos += 1
|
|---|
| 770 | xtics_str += ")"
|
|---|
| 771 |
|
|---|
| 772 | n = 1
|
|---|
| 773 | plot_str = "newhistogram \"\""
|
|---|
| 774 | for prot in joint_protocols:
|
|---|
| 775 | plot_str += ", \\\n " + "'" + data_metric_filename + "'" + " using " + str(n) + " lc rgb " + colors[n] + " title \"" + m_metric_name[metric] + " for " + m_prot_name[prot] + "\""
|
|---|
| 776 | n += 1
|
|---|
| 777 |
|
|---|
| 778 | ylabel_str = "%(m)s" % dict(m = m_metric_name[metric])
|
|---|
| 779 | 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)
|
|---|
| 780 |
|
|---|
| 781 | create_file(gp_metric_filename, content)
|
|---|
| 782 |
|
|---|
| 783 | # Creating the data file
|
|---|
| 784 | content = "#" + metric
|
|---|
| 785 | content += "\n"
|
|---|
| 786 | for app in apps:
|
|---|
| 787 | if app != apps[0]:
|
|---|
| 788 | for prot in joint_protocols:
|
|---|
| 789 | for p in joint_protocols:
|
|---|
| 790 | content += "%-15f " % 0.0
|
|---|
| 791 | content += "\n"
|
|---|
| 792 | for i in nb_procs:
|
|---|
| 793 | for prot in joint_protocols:
|
|---|
| 794 | for p in joint_protocols:
|
|---|
| 795 | if p != prot:
|
|---|
| 796 | content += "%-15f " % 0
|
|---|
| 797 | else:
|
|---|
| 798 | content += "%-15f " % (float(metrics_val[prot][app][i][metric]))
|
|---|
| 799 | content += "\n"
|
|---|
| 800 | if i != nb_procs[-1]:
|
|---|
| 801 | for p in joint_protocols:
|
|---|
| 802 | content += "%-15f " % 0.0
|
|---|
| 803 | content += "\n"
|
|---|
| 804 |
|
|---|
| 805 | create_file(data_metric_filename, content)
|
|---|
| 806 | # Calling gnuplot
|
|---|
| 807 | print "gnuplot", gp_metric_filename
|
|---|
| 808 | subprocess.call([ 'gnuplot', gp_metric_filename ])
|
|---|
| 809 |
|
|---|
| 810 |
|
|---|
| 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 |
|
|---|
