1 #! /usr/bin/env python

2 # -*- coding: utf-8 -*-

3

4 import sys

5 from re import match, search

6 from pprint import pformat

7 from datetime import datetime

8 from subprocess import call,Popen,PIPE

9

10 """

11 This script generates a graph that represents the overhead

12

13 involved in synchronisation operations

14 This script generates results for 5 runs per threads and iteration in

15 TOTAL_THREADS_TABLE and ITER_PER_TASK_TABLE

16 """

17

18 usage="""

19 This runs the exec time vs task size in three levels of loop nest. The outer most iterates through

20 a selection of numbers-of-thread. For each of those, the next lever iterates over a number of work-loops-per-task

21 values. The innermost repeats several times and chooses the best.

22 Finally, it generates an output file for each value of number-of-threads that give the number of all runs.

23 It is expected that the output directory's path is meaningful, such as machine-name, date, and so on

24 Usage:

25 %s [executable binary] [path to output dir]

26 """ % sys.argv[0]

27

28 NUM_CORES = 4 #Number of Cores the code was compiled for

29 ITERS_PER_TASK_TABLE = [2, 5, 10, 20, 40, 80, 160, 320, 640] #Number of iterations of inner loop

30 TASKS_PER_THREAD = 30000 #Number of interations of outer loop

31 TOTAL_THREADS_TABLE = [8, 32, 128, 512]

32

33 def getNumber(line):

34 match_obj = search("(\d+\.?\d*)", line)

35 if match_obj != None:

36 return match_obj.groups()[0]

37 else:

38 raise ValueError

39

40 if len(sys.argv) != 3:

41 print usage

42 sys.exit(0)

43

44 cmd=sys.argv[1]

45 try:

46 f = open(cmd)

47 except IOError:

48 print "Please provide a valid executable."

49 f.close()

50 sys.exit(1)

51 finally:

52 f.close()

53

54 output_dir_path = sys.argv[2]

55

56 #===================================================================

57 # Done with parsing cmd line inputs, start doing the runs

58 #

59

60 for totalThreads in TOTAL_THREADS_TABLE:

61 print "\nDoing run with %d threads" % totalThreads

62 output = "%s/%d_thds__o%d__perfCtrs.meas" % (output_dir_path, totalThreads, TASKS_PER_THREAD)

63 print "output file: %s" % output

64 threadsPerCore = totalThreads/NUM_CORES

65 array_of_results = {}

66 for workload_iterations_in_task in ITERS_PER_TASK_TABLE:

67 print "Run for %s workload iterations in a task" % workload_iterations_in_task

68 results = []

69 for run in range(5):

70 print "Run %d" % run,

71 program_output = Popen("%s -t %d -i %d -o %d" % (cmd,

72 totalThreads,

73 workload_iterations_in_task,

74 TASKS_PER_THREAD),

75 stdout=PIPE, stderr=None, shell=True).stdout.read()

76 #parse arguments for

77 for line in program_output.split("\n"):

78 if match("^Sum across threads of work cycles:", line) != None:

79 total_workcycles = int(getNumber(line))

80 if match("^Total Execution Cycles:", line) != None:

81 total_exe_cycles = int(getNumber(line))

82 if match("^ExeCycles/WorkCycles Ratio", line) != None:

83 exeCycles_workCycles_ratio = float(getNumber(line))

84 results.append({"total_workcycles" : total_workcycles,

85 "total_exe_cycles" : total_exe_cycles,

86 "exeCycles_workCycles_ratio" : exeCycles_workCycles_ratio})

87 print "ratio %f" % exeCycles_workCycles_ratio

88 array_of_results[workload_iterations_in_task] = results

89

90 #open file to output data

91 try:

92 data_output = open(output,"w")

93 except IOError:

94 print "Cannot open output file %s" % output

95 sys.exit(1)

96

97 #output relevant data to file

98 data_output.write(";\n".join(["# This is a output of the overhead_data_generation.py script, run the overhead_result_calc.py script to get the calculated results",

99 "data_filename = " + pformat(output),

100 "NUM_CORES = " + pformat(NUM_CORES),

101 "ITERS_PER_TASK_TABLE = " + pformat(ITERS_PER_TASK_TABLE),

102 "TASKS_PER_THREAD = " + pformat(TASKS_PER_THREAD),

103 "date_of_run = " + pformat(datetime.now()),

104 "threads_per_core = " + pformat(threadsPerCore),

105 "totalThreads = " + pformat(totalThreads),

106 "# array_of_results: hash key is the number of iterations per task(inner iterations)",

107 "array_of_results = " + pformat(array_of_results)]))

108

109

110 data_output.close()

111