TrafficGen.py revision 13665
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355759Shsul@eecs.umich.edu#
362454SN/A# Authors: Thomas Grass
372680Sktlim@umich.edu#          Andreas Hansson
385759Shsul@eecs.umich.edu#          Sascha Bischoff
395759Shsul@eecs.umich.edu
402474SN/Afrom m5.params import *
412207SN/Afrom m5.objects.BaseTrafficGen import *
422474SN/A
432474SN/A# The behaviour of this traffic generator is specified in a
442474SN/A# configuration file, and this file describes a state transition graph
455569Snate@binkert.org# where each state is a specific generator behaviour. Examples include
465569Snate@binkert.org# idling, generating linear address sequences, random sequences and
475154Sgblack@eecs.umich.edu# replay of captured traces. By describing these behaviours as states,
482474SN/A# it is straight forward to create very complex behaviours, simply by
492474SN/A# arranging them in graphs. The graph transitions can also be
502474SN/A# annotated with probabilities, effectively making it a Markov Chain.
512474SN/Aclass TrafficGen(BaseTrafficGen):
522474SN/A    type = 'TrafficGen'
532474SN/A    cxx_header = "cpu/testers/traffic_gen/traffic_gen.hh"
542474SN/A
552474SN/A    # Config file to parse for the state descriptions
562474SN/A    config_file = Param.String("Configuration file describing the behaviour")
572474SN/A