litmus-rt.git - The LITMUS^RT kernel.

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author	Randy Dunlap <randy.dunlap@oracle.com>	2008-11-21 19:59:57 -0500
committer	Ingo Molnar <mingo@elte.hu>	2008-11-23 04:52:45 -0500
commit	2ed1cdcf9a83205d1343f29b630abff232eaa72c (patch)
tree	97304ced8d05b5b7497e37b661abbce4540f0194 /net/lapb/lapb_timer.c
parent	9f1441644213e5f6faa150206399fe511eba2eb6 (diff)

irq.h: fix missing/extra kernel-doc

Impact: fix kernel-doc build Fix missing & excess irq.h kernel-doc: Warning(include/linux/irq.h:182): No description found for parameter 'irq' Warning(include/linux/irq.h:182): Excess struct/union/enum/typedef member 'affinity_entry' description in 'irq_desc' Signed-off-by: Randy Dunlap <randy.dunlap@oracle.com> Cc: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Ingo Molnar <mingo@elte.hu>

Diffstat (limited to 'net/lapb/lapb_timer.c')

0 files changed, 0 insertions, 0 deletions

#!/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 paule@rapitasystems.com or robdavis@cs.york.ac.uk if you have any questions regarding this software. """ import numpy import optparse import sys import textwrap from schedcat.model.tasks import TaskSystem import schedcat.model.tasks as tasks from schedcat.model.tasks import SporadicTask from schedcat.util.time import ms2us from schedcat.overheads.jlfp import quantize_params NAMED_PERIODS = { 'uni-short' : (3, 33), 'uni-moderate' : (10, 100), 'uni-long' : (50, 250), } NAMED_PERIOD_DISTRIBUTIONS = [ "logunif", "unif", ] 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 # wrapper for generating task sets for use within the schedcat library # parameters: # periods: one from NAMED_PERIODS (period definitions similar to those used in tasksets.py # period_distribution: 'unif' or 'logunif' for uniform or log-based distribution # tasks_n: number of tasks to be generated # utilization: target utilization of the task set to be generated def gen_taskset(periods, period_distribution, tasks_n, utilization, period_granularity=None, scale=ms2us, want_integral=True): if periods in NAMED_PERIODS: # Look up by name. (period_min, period_max) = NAMED_PERIODS[periods] else: # If unknown, then assume caller specified range manually. (period_min, period_max) = periods x = StaffordRandFixedSum(tasks_n, utilization, 1) if period_granularity is None: period_granularity = period_min periods = gen_periods(tasks_n, 1, period_min, period_max, period_granularity, period_distribution) ts = TaskSystem() periods = numpy.maximum(periods[0], max(period_min, period_granularity)) C = scale(x[0] * periods) taskset = numpy.c_[x[0], C / periods, periods, C] for t in range(numpy.size(taskset,0)): ts.append(SporadicTask(taskset[t][3], scale(taskset[t][2]))) if want_integral: quantize_params(ts) return ts def gen_tasksets(options): x = StaffordRandFixedSum(options.n, options.util, 1) periods = gen_periods(options.n, 1, options.permin, options.permax, options.pergran, options.perdist) ts = TaskSystem() C = x[0] * periods[0] if options.round_C: C = numpy.round(C, decimals=0) elif options.floor_C: C = numpy.floor(C) taskset = numpy.c_[x[0], C / periods[0], periods[0], C] for t in range(numpy.size(taskset,0)): ts.append(SporadicTask(taskset[t][3], taskset[t][2])) # print ts return ts def gcd(a, b): # From http://stackoverflow.com/a/147539 """Return greatest common divisor using Euclid's Algorithm.""" while b: a, b = b, a % b return a def lcm(a, b): # From http://stackoverflow.com/a/147539 """Return lowest common multiple.""" return a * b // gcd(a, b) def print_taskset(taskset, format): util = .0 # Total utilization hp = 1 # Hyperperiod for t in range(numpy.size(taskset,0)): util += taskset[t][1] hp = lcm(hp, taskset[t][2]) print "<taskset>" print "<properties hyperperiod=\"%d\" utilization=\"%.10f\" />" % (hp, util) for t in range(numpy.size(taskset,0)): #data = { 'Ugen' : taskset[t][0], 'U' : taskset[t][1], 'T' : taskset[t][2], 'C' : taskset[t][3] } print "<task wcet=\"%.10f\" period=\"%d\" utilization=\"%.10f\"/>" % (taskset[t][3], taskset[t][2], taskset[t][1]) print "</taskset>" 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]") parser.add_option("--floor-C", action="store_true", dest="floor_C", default=False, help="Floor() execution times [%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 = '%(Ugen)f %(U)f %(C).2f %(T)d\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())


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