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
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
|
# Copyright (c) 2005 The Regents of The University of Michigan
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer;
# 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;
# neither the name of the copyright holders nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "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 COPYRIGHT
# OWNER 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.
#
# Authors: Nathan Binkert
from orderdict import orderdict
import output
class FileData(dict):
def __init__(self, filename):
self.filename = filename
fd = file(filename)
current = []
for line in fd:
line = line.strip()
if line.startswith('>>>'):
current = []
self[line[3:]] = current
else:
current.append(line)
fd.close()
class RunData(dict):
def __init__(self, filename):
self.filename = filename
def __getattribute__(self, attr):
if attr == 'total':
total = 0.0
for value in self.itervalues():
total += value
return total
if attr == 'filedata':
return FileData(self.filename)
if attr == 'maxsymlen':
return max([ len(sym) for sym in self.iterkeys() ])
return super(RunData, self).__getattribute__(attr)
def display(self, output=None, limit=None, maxsymlen=None):
if not output:
import sys
output = sys.stdout
elif isinstance(output, str):
output = file(output, 'w')
total = float(self.total)
# swap (string,count) order so we can sort on count
symbols = [ (count,name) for name,count in self.iteritems() ]
symbols.sort(reverse=True)
if limit is not None:
symbols = symbols[:limit]
if not maxsymlen:
maxsymlen = self.maxsymlen
symbolf = "%-" + str(maxsymlen + 1) + "s %.2f%%"
for number,name in symbols:
print >>output, symbolf % (name, 100.0 * (float(number) / total))
class PCData(RunData):
def __init__(self, filename=None, categorize=None, showidle=True):
super(PCData, self).__init__(self, filename)
filedata = self.filedata['PC data']
for line in filedata:
(symbol, count) = line.split()
if symbol == "0x0":
continue
count = int(count)
if categorize is not None:
category = categorize(symbol)
if category is None:
category = 'other'
elif category == 'idle' and not showidle:
continue
self[category] = count
class FuncNode(object):
def __new__(cls, filedata=None):
if filedata is None:
return super(FuncNode, cls).__new__(cls)
nodes = {}
for line in filedata['function data']:
data = line.split(' ')
node_id = long(data[0], 16)
node = FuncNode()
node.symbol = data[1]
if node.symbol == '':
node.symbol = 'unknown'
node.count = long(data[2])
node.children = [ long(child, 16) for child in data[3:] ]
nodes[node_id] = node
for node in nodes.itervalues():
children = []
for cid in node.children:
child = nodes[cid]
children.append(child)
child.parent = node
node.children = tuple(children)
if not nodes:
print filedata.filename
print nodes
return nodes[0]
def total(self):
total = self.count
for child in self.children:
total += child.total()
return total
def aggregate(self, dict, categorize, incategory):
category = None
if categorize:
category = categorize(self.symbol)
total = self.count
for child in self.children:
total += child.aggregate(dict, categorize, category or incategory)
if category:
dict[category] = dict.get(category, 0) + total
return 0
elif not incategory:
dict[self.symbol] = dict.get(self.symbol, 0) + total
return total
def dump(self):
kids = [ child.symbol for child in self.children]
print '%s %d <%s>' % (self.symbol, self.count, ', '.join(kids))
for child in self.children:
child.dump()
def _dot(self, dot, threshold, categorize, total):
from pydot import Dot, Edge, Node
self.dot_node = None
value = self.total() * 100.0 / total
if value < threshold:
return
if categorize:
category = categorize(self.symbol)
if category and category != 'other':
return
label = '%s %.2f%%' % (self.symbol, value)
self.dot_node = Node(self, label=label)
dot.add_node(self.dot_node)
for child in self.children:
child._dot(dot, threshold, categorize, total)
if child.dot_node is not None:
dot.add_edge(Edge(self, child))
def _cleandot(self):
for child in self.children:
child._cleandot()
self.dot_node = None
del self.__dict__['dot_node']
def dot(self, dot, threshold=0.1, categorize=None):
self._dot(dot, threshold, categorize, self.total())
self._cleandot()
class FuncData(RunData):
def __init__(self, filename, categorize=None):
super(FuncData, self).__init__(filename)
tree = self.tree
tree.aggregate(self, categorize, incategory=False)
self.total = tree.total()
def __getattribute__(self, attr):
if attr == 'tree':
return FuncNode(self.filedata)
return super(FuncData, self).__getattribute__(attr)
def displayx(self, output=None, maxcount=None):
if output is None:
import sys
output = sys.stdout
items = [ (val,key) for key,val in self.iteritems() ]
items.sort(reverse=True)
for val,key in items:
if maxcount is not None:
if maxcount == 0:
return
maxcount -= 1
percent = val * 100.0 / self.total
print >>output, '%-30s %8s' % (key, '%3.2f%%' % percent)
class Profile(object):
# This list controls the order of values in stacked bar data output
default_categories = [ 'interrupt',
'driver',
'stack',
'buffer',
'copy',
'syscall',
'user',
'other',
'idle']
def __init__(self, datatype, categorize=None):
categories = Profile.default_categories
self.datatype = datatype
self.categorize = categorize
self.data = {}
self.categories = categories[:]
self.rcategories = categories[:]
self.rcategories.reverse()
self.cpu = 0
# Read in files
def inputdir(self, directory):
import os, os.path, re
from os.path import expanduser, join as joinpath
directory = expanduser(directory)
label_ex = re.compile(r'profile\.(.*).dat')
for root,dirs,files in os.walk(directory):
for name in files:
match = label_ex.match(name)
if not match:
continue
filename = joinpath(root, name)
prefix = os.path.commonprefix([root, directory])
dirname = root[len(prefix)+1:]
data = self.datatype(filename, self.categorize)
self.setdata(dirname, match.group(1), data)
def setdata(self, run, cpu, data):
if run not in self.data:
self.data[run] = {}
if cpu in self.data[run]:
raise AttributeError, \
'data already stored for run %s and cpu %s' % (run, cpu)
self.data[run][cpu] = data
def getdata(self, run, cpu):
try:
return self.data[run][cpu]
except KeyError:
print run, cpu
return None
def alldata(self):
for run,cpus in self.data.iteritems():
for cpu,data in cpus.iteritems():
yield run,cpu,data
def get(self, job, stat, system=None):
if system is None and hasattr('system', job):
system = job.system
if system is None:
raise AttributeError, 'The job must have a system set'
cpu = '%s.run%d' % (system, self.cpu)
data = self.getdata(str(job), cpu)
if not data:
return None
values = []
for category in self.categories:
val = float(data.get(category, 0.0))
if val < 0.0:
raise ValueError, 'value is %f' % val
values.append(val)
total = sum(values)
return [ v / total * 100.0 for v in values ]
def dump(self):
for run,cpu,data in self.alldata():
print 'run %s, cpu %s' % (run, cpu)
data.dump()
print
def write_dot(self, threshold, jobfile=None, jobs=None):
import pydot
if jobs is None:
jobs = [ job for job in jobfile.jobs() ]
for job in jobs:
cpu = '%s.run%d' % (job.system, self.cpu)
symbols = self.getdata(job.name, cpu)
if not symbols:
continue
dot = pydot.Dot()
symbols.tree.dot(dot, threshold=threshold)
dot.write(symbols.filename[:-3] + 'dot')
def write_txt(self, jobfile=None, jobs=None, limit=None):
if jobs is None:
jobs = [ job for job in jobfile.jobs() ]
for job in jobs:
cpu = '%s.run%d' % (job.system, self.cpu)
symbols = self.getdata(job.name, cpu)
if not symbols:
continue
output = file(symbols.filename[:-3] + 'txt', 'w')
symbols.display(output, limit)
def display(self, jobfile=None, jobs=None, limit=None):
if jobs is None:
jobs = [ job for job in jobfile.jobs() ]
maxsymlen = 0
thejobs = []
for job in jobs:
cpu = '%s.run%d' % (job.system, self.cpu)
symbols = self.getdata(job.name, cpu)
if symbols:
thejobs.append(job)
maxsymlen = max(maxsymlen, symbols.maxsymlen)
for job in thejobs:
cpu = '%s.run%d' % (job.system, self.cpu)
symbols = self.getdata(job.name, cpu)
print job.name
symbols.display(limit=limit, maxsymlen=maxsymlen)
print
from categories import func_categorize, pc_categorize
class PCProfile(Profile):
def __init__(self, categorize=pc_categorize):
super(PCProfile, self).__init__(PCData, categorize)
class FuncProfile(Profile):
def __init__(self, categorize=func_categorize):
super(FuncProfile, self).__init__(FuncData, categorize)
def usage(exitcode = None):
print '''\
Usage: %s [-bc] [-g <dir>] [-j <jobfile>] [-n <num>]
-c groups symbols into categories
-b dumps data for bar charts
-d generate dot output
-g <d> draw graphs and send output to <d>
-j <jobfile> specify a different jobfile (default is Test.py)
-n <n> selects number of top symbols to print (default 5)
''' % sys.argv[0]
if exitcode is not None:
sys.exit(exitcode)
if __name__ == '__main__':
import getopt, re, sys
from os.path import expanduser
from output import StatOutput
# default option values
numsyms = 10
graph = None
cpus = [ 0 ]
categorize = False
showidle = True
funcdata = True
jobfilename = 'Test.py'
dodot = False
dotfile = None
textout = False
threshold = 0.01
inputfile = None
try:
opts, args = getopt.getopt(sys.argv[1:], 'C:cdD:f:g:ij:n:pT:t')
except getopt.GetoptError:
usage(2)
for o,a in opts:
if o == '-C':
cpus = [ int(x) for x in a.split(',') ]
elif o == '-c':
categorize = True
elif o == '-D':
dotfile = a
elif o == '-d':
dodot = True
elif o == '-f':
inputfile = expanduser(a)
elif o == '-g':
graph = a
elif o == '-i':
showidle = False
elif o == '-j':
jobfilename = a
elif o == '-n':
numsyms = int(a)
elif o == '-p':
funcdata = False
elif o == '-T':
threshold = float(a)
elif o == '-t':
textout = True
if args:
print "'%s'" % args, len(args)
usage(1)
if inputfile:
catfunc = None
if categorize:
catfunc = func_categorize
data = FuncData(inputfile, categorize=catfunc)
if dodot:
import pydot
dot = pydot.Dot()
data.tree.dot(dot, threshold=threshold)
#dot.orientation = 'landscape'
#dot.ranksep='equally'
#dot.rank='samerank'
dot.write(dotfile, format='png')
else:
data.display(limit=numsyms)
else:
from jobfile import JobFile
jobfile = JobFile(jobfilename)
if funcdata:
profile = FuncProfile()
else:
profile = PCProfile()
if not categorize:
profile.categorize = None
profile.inputdir(jobfile.rootdir)
if graph:
for cpu in cpus:
profile.cpu = cpu
if funcdata:
name = 'funcstacks%d' % cpu
else:
name = 'stacks%d' % cpu
output = StatOutput(jobfile, info=profile)
output.xlabel = 'System Configuration'
output.ylabel = '% CPU utilization'
output.stat = name
output.graph(name, graph)
if dodot:
for cpu in cpus:
profile.cpu = cpu
profile.write_dot(jobfile=jobfile, threshold=threshold)
if textout:
for cpu in cpus:
profile.cpu = cpu
profile.write_txt(jobfile=jobfile)
if not graph and not textout and not dodot:
for cpu in cpus:
if not categorize:
profile.categorize = None
profile.cpu = cpu
profile.display(jobfile=jobfile, limit=numsyms)
|