Mercurial > cgi-bin > hgwebdir.cgi > VMS > 2__runs_and_data
view scripts/overhead_result_calc.py @ 15:db3409eab322
exec_time_vs_task_size: data generation script for xoanon, because of higher core count
| author | Merten Sach <msach@mailbox.tu-berlin.de> |
|---|---|
| date | Mon, 06 Feb 2012 16:29:36 +0100 |
| parents | |
| children |
line source
1 #! /usr/bin/env python
2 # -*- coding: utf-8 -*-
4 import sys
5 from re import search
6 import datetime
7 from os.path import basename
9 """
10 This script generates a graph that represents the overhead
11 involved in synchronisation operations
12 """
14 usage="""
15 This generates an output file for each value of number-of-threads that give the number of all runs.
16 As an input it expects a result file which is generated by the overhead_result_calc.py script.
17 The file extension of the result file has to be ".meas".
18 It is expected that the output directory's path is meaningful, such as machine-name, date, and so on
19 Usage:
20 %s [result files] [path to output dir]
21 """ % sys.argv[0]
23 if len(sys.argv) < 3:
24 print usage
25 sys.exit(0)
27 result_filenames = sys.argv[1:-1]
28 output_dir_path = sys.argv[-1]
30 for result_filename in result_filenames:
31 #open input file
32 try:
33 result_file = open(result_filename,"r")
34 except:
35 print "Cannot open result file %s" % result_filename
36 sys.exit(1)
38 #parse(evaluate) result file
39 try:
40 exec(result_file.read())
41 except:
42 print "Cannot parse result file: %s" % result_filename
43 result_file.close()
44 sys.exit(1)
45 result_file.close()
47 #check for file extension
48 result_filename = basename(result_filename)
49 if search("\.meas$",result_filename) == None:
50 print "Wrong file extension! Has to be '.meas'"
51 sys.exit(1)
53 output = output_dir_path + "/" + result_filename.replace(".meas",".result")
54 #open gnuplot output
55 try:
56 gnuplot_output = open(output,"w")
57 except IOError:
58 print "Cannot open output file %s" % output
59 result_file.close()
60 sys.exit(1)
62 table_header = "# %20s\t%20s\t%20s\t%20s\t%20s\t%20s\t%20s\t%20s\n" % (
63 "<iters per task>",
64 "<total exe cycles>",
65 "<total work cyc>",
66 "<one task cyc>",
67 "<total overhead cyc>",
68 "<num syncs>",
69 "<overhead per Sync cyc>",
70 "<Exe/Work ratio>")
72 #write header to file
73 gnuplot_output.writelines(["# Output file name: %s\n" % data_filename,
74 "# Date of Run: %s\n" % date_of_run,
75 "# Number of Cores: %d\n" % NUM_CORES,
76 "# Number of Threads: %f per Core, %d total\n" % (threads_per_core, totalThreads),
77 table_header,
78 "# " + (len(table_header)-3)*"-" + "\n"])
80 #Now print the results out
81 for workload_iterations_in_task in ITERS_PER_TASK_TABLE:
82 results = array_of_results[workload_iterations_in_task]
84 #take shortest run
85 results.sort(lambda x,y: cmp(x["total_exe_cycles"],y["total_exe_cycles"]))
86 total_workcycles = results[0]["total_workcycles"]
87 total_exe_cycles = results[0]["total_exe_cycles"]
88 #exeCycles_workCycles_ratio = results[0]["exeCycles_workCycles_ratio"]
90 #Calculate numbers
91 overhead = total_exe_cycles - total_workcycles
92 total_syncs = totalThreads * TASKS_PER_THREAD * 2
93 overhead_per_sync = float(overhead) / float(total_syncs)
94 cycles_of_task = float(total_workcycles) / float(TASKS_PER_THREAD * totalThreads)
95 overhead_per_core = float(overhead) / NUM_CORES
96 workcycles_per_core = total_workcycles / NUM_CORES
98 # The 2 is in there because we have two sync operations in one per outer iteration
99 exeCycles_workCycles_ratio = float(total_workcycles+float(overhead)/2)/float(total_workcycles)
101 gnuplot_output.write("%20d\t%20d\t%20d\t%20f\t%20d\t%20d\t%20f\t%20f\n" % (
102 workload_iterations_in_task,
103 total_exe_cycles,
104 total_workcycles,
105 cycles_of_task,
106 overhead,
107 total_syncs,
108 overhead_per_sync,
109 exeCycles_workCycles_ratio))
111 gnuplot_output.close();