-
Notifications
You must be signed in to change notification settings - Fork 0
/
taskgen.py
executable file
·308 lines (241 loc) · 12.3 KB
/
taskgen.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
#!/usr/bin/python
"""A taskset generator for experiments with real-time task sets
Copyright 2010 Paul Emberson, Roger Stafford, Robert Davis.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY EXPRESS
OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
EVENT SHALL THE AUTHORS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA,
OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
The views and conclusions contained in the software and documentation are
those of the authors and should not be interpreted as representing official
policies, either expressed or implied, of Paul Emberson, Roger Stafford or
Robert Davis.
Includes Python implementation of Roger Stafford's randfixedsum implementation
http://www.mathworks.com/matlabcentral/fileexchange/9700
Adapted specifically for the purpose of taskset generation with fixed
total utilisation value
Please contact [email protected] or [email protected] if you have
any questions regarding this software.
"""
import numpy
import optparse
import sys
import textwrap
def StaffordRandFixedSum(n, u, nsets):
#deal with n=1 case
if n == 1:
return numpy.tile(numpy.array([u]),[nsets,1])
k = numpy.floor(u)
s = u
step = 1 if k < (k-n+1) else -1
s1 = s - numpy.arange( k, (k-n+1)+step, step )
step = 1 if (k+n) < (k-n+1) else -1
s2 = numpy.arange( (k+n), (k+1)+step, step ) - s
tiny = numpy.finfo(float).tiny
huge = numpy.finfo(float).max
w = numpy.zeros((n, n+1))
w[0,1] = huge
t = numpy.zeros((n-1,n))
for i in numpy.arange(2, (n+1)):
tmp1 = w[i-2, numpy.arange(1,(i+1))] * s1[numpy.arange(0,i)]/float(i)
tmp2 = w[i-2, numpy.arange(0,i)] * s2[numpy.arange((n-i),n)]/float(i)
w[i-1, numpy.arange(1,(i+1))] = tmp1 + tmp2;
tmp3 = w[i-1, numpy.arange(1,(i+1))] + tiny;
tmp4 = numpy.array( (s2[numpy.arange((n-i),n)] > s1[numpy.arange(0,i)]) )
t[i-2, numpy.arange(0,i)] = (tmp2 / tmp3) * tmp4 + (1 - tmp1/tmp3) * (numpy.logical_not(tmp4))
m = nsets
x = numpy.zeros((n,m))
rt = numpy.random.uniform(size=(n-1,m)) #rand simplex type
rs = numpy.random.uniform(size=(n-1,m)) #rand position in simplex
s = numpy.repeat(s, m);
j = numpy.repeat(int(k+1), m);
sm = numpy.repeat(0, m);
pr = numpy.repeat(1, m);
for i in numpy.arange(n-1,0,-1): #iterate through dimensions
e = ( rt[(n-i)-1,...] <= t[i-1,j-1] ) #decide which direction to move in this dimension (1 or 0)
sx = rs[(n-i)-1,...] ** (1/float(i)) #next simplex coord
sm = sm + (1-sx) * pr * s/float(i+1)
pr = sx * pr
x[(n-i)-1,...] = sm + pr * e
s = s - e
j = j - e #change transition table column if required
x[n-1,...] = sm + pr * s
#iterated in fixed dimension order but needs to be randomised
#permute x row order within each column
for i in xrange(0,m):
x[...,i] = x[numpy.random.permutation(n),i]
return numpy.transpose(x);
def gen_periods(n, nsets, min, max, gran, dist):
if dist == "logunif":
periods = numpy.exp(numpy.random.uniform(low=numpy.log(min), high=numpy.log(max+gran), size=(nsets,n)))
elif dist == "unif":
periods = numpy.random.uniform(low=min, high=(max+gran), size=(nsets,n))
else:
return None
periods = numpy.floor(periods / gran) * gran
return periods
def gen_tasksets(options):
x = StaffordRandFixedSum(options.n, options.util, options.nsets)
periods = gen_periods(options.n, options.nsets, options.permin, options.permax, options.pergran, options.perdist)
#iterate through each row (which represents utils for a taskset)
for i in range(numpy.size(x, axis=0)):
C = x[i] * periods[i]
if options.round_C:
C = numpy.round(C, decimals=0)
taskset = numpy.c_[x[i], C / periods[i], periods[i], C]
print_taskset(taskset, options.format, i)
print ""
def print_taskset(taskset, format, tsn):
header = """{
"resources" : 0,
"tasks" : {\n"""
footer1 = """ },
\"global\" : {"""
policy ="""\n\t\t\"default_policy\" : \"SCHED_DEADLINE\","""
footer2 = """\n\t\t\"duration\" : 10,
\"logdir\" : \"/tmp/\",
\"log_basename\" : \"rt-app\",
\"lock_pages\" : true
}
}"""
outfile = open('GTS'+str(tsn)+'_'+str(numpy.size(taskset,0))+'tsk.txt', 'w')
outfile.write(header)
for t in range(numpy.size(taskset,0)):
data = { 'N' : str(t+1), 'Ugen' : taskset[t][0], 'U' : taskset[t][1], 'T' : taskset[t][2], 'C' : taskset[t][3] }
outfile.write("\t\t\"task" + str(t+1) + "\" : {\n")
outfile.write("\t\t\t\"exec\" : " + str(int(taskset[t][3])) + ",\n")
outfile.write("\t\t\t\"period\" : " + str(int(taskset[t][2])) + ",\n")
outfile.write("\t\t\t\"deadline\" : " + str(int(taskset[t][2])) + "\n")
outfile.write("\t\t},\n")
outfile.write("\t\t}\n")
outfile.write(footer1)
outfile.write(policy)
outfile.write(footer2)
def main():
usage_str = "%prog [options]"
description_str = "This is a taskset generator intended for generating data for experiments with real-time schedulability tests and design space exploration tools. The utilisation generation is done using Roger Stafford's randfixedsum algorithm. A paper describing this tool was published at the WATERS 2010 workshop. Copyright 2010 Paul Emberson, Roger Stafford, Robert Davis. All rights reserved. Run %prog --about for licensing information."
epilog_str = "Examples:"
#don't add help option as we will handle it ourselves
parser = optparse.OptionParser(usage=usage_str,
description=description_str,
epilog=epilog_str,
add_help_option=False,
version="%prog version 0.1")
parser.add_option("-h", "--help", action="store_true", dest="help",
default=False,
help="Show this help message and exit")
parser.add_option("--about", action="store_true", dest="about",
default=False,
help="See licensing and other information about this software")
parser.add_option("-u", "--taskset-utilisation",
metavar="UTIL", type="float", dest="util",
default="0.75",
help="Set total taskset utilisation to UTIL [%default]")
parser.add_option("-n", "--num-tasks",
metavar="N", type="int", dest="n",
default="5",
help="Produce tasksets of size N [%default]")
parser.add_option("-s", "--num-sets",
metavar="SETS", type="int", dest="nsets",
default="3",
help="Produce SETS tasksets [%default]")
parser.add_option("-d", "--period-distribution",
metavar="PDIST", type="string", dest="perdist",
default="logunif",
help="Choose period distribution to be 'unif' or 'logunif' [%default]")
parser.add_option("-p", "--period-min",
metavar="PMIN", type="int", dest="permin",
default="1000",
help="Set minimum period value to PMIN [%default]")
parser.add_option("-q", "--period-max",
metavar="PMAX", type="int", dest="permax",
default=None,
help="Set maximum period value to PMAX [PMIN]")
parser.add_option("-g", "--period-gran",
metavar="PGRAN", type="int", dest="pergran",
default=None,
help="Set period granularity to PGRAN [PMIN]")
parser.add_option("--round-C", action="store_true", dest="round_C",
default=False,
help="Round execution times to nearest integer [%default]")
format_default = '%(Ugen)f %(U)f %(C).2f %(T)d\\n';
format_help = "Specify output format as a Python template string. The following variables are available: Ugen - the task utilisation value generated by Stafford's randfixedsum algorithm, T - the generated task period value, C - the generated task execution time, U - the actual utilisation equal to C/T which will differ from Ugen if the --round-C option is used. See below for further examples. A new line is always inserted between tasksets. [" + format_default + "]"
parser.add_option("-f", "--output-format",
metavar="FORMAT", type="string", dest="format",
default = 'task%(N)s\t%(C)d\t\t%(T)d\t-\n',
help=format_help)
(options, args) = parser.parse_args()
if options.about:
print __doc__
return 0
if options.help:
print_help(parser)
return 0
if options.n < 1:
print >>sys.stderr, "Minimum number of tasks is 1"
return 1
if options.util > options.n:
print >>sys.stderr, "Taskset utilisation must be less than or equal to number of tasks"
return 1
if options.nsets < 1:
print >>sys.stderr, "Minimum number of tasksets is 1"
return 1
known_perdists = ["unif", "logunif"]
if options.perdist not in known_perdists:
print >>sys.stderr, "Period distribution must be one of " + str(known_perdists)
return 1
if options.permin <= 0:
print >>sys.stderr, "Period minimum must be greater than 0"
return 1
#permax = None is default. Set to permin in this case
if options.permax == None:
options.permax = options.permin
if options.permin > options.permax:
print >>sys.stderr, "Period maximum must be greater than or equal to minimum"
return 1
#pergran = None is default. Set to permin in this case
if options.pergran == None:
options.pergran = options.permin
if options.pergran < 1:
print >>sys.stderr, "Period granularity must be an integer greater than equal to 1"
return 1
if (options.permax % options.pergran) != 0:
print >>sys.stderr, "Period maximum must be a integer multiple of period granularity"
return 1
if (options.permin % options.pergran) != 0:
print >>sys.stderr, "Period minimum must be a integer multiple of period granularity"
return 1
options.format = options.format.replace("\\n", "\n")
gen_tasksets(options)
return 0
def print_help(parser):
parser.print_help();
print ""
example_desc = \
"Generate 5 tasksets of 10 tasks with loguniform periods " +\
"between 1000 and 100000. Round execution times and output "+\
"a table of execution times and periods."
print textwrap.fill(example_desc, 75)
print " " +parser.get_prog_name() + " -s 5 -n 10 -p 1000 -q 100000 -d logunif --round-C -f \"%(C)d %(T)d\\n\""
print ""
example_desc = \
"Print utilisation values from Stafford's randfixedsum " +\
"for 20 tasksets of 8 tasks, with one line per taskset, " +\
"rounded to 3 decimal places:"
print textwrap.fill(example_desc, 75)
print " " + parser.get_prog_name() + " -s 20 -n 8 -f \"%(Ugen).3f\""
if __name__ == "__main__":
sys.exit(main())