02d2d7b1e0
The Loop Predictor implementation is now a SimObject so that other branch predictors can easily use it (including LTAGE, which is now using it). It has also been updated with the latest available loop predictor implementation from Andre Seznec: http://www.irisa.fr/alf/downloads/seznec/TAGE-GSC-IMLI.tar Change-Id: I60ad079a2c49b00a1f84d5cfd3611631883a4b57 Reviewed-on: https://gem5-review.googlesource.com/c/15775 Reviewed-by: Andreas Sandberg <andreas.sandberg@arm.com> Maintainer: Andreas Sandberg <andreas.sandberg@arm.com>
200 lines
8.3 KiB
Python
200 lines
8.3 KiB
Python
# Copyright (c) 2012 Mark D. Hill and David A. Wood
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# Copyright (c) 2015 The University of Wisconsin
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are
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# met: redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer;
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# redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution;
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# neither the name of the copyright holders nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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# Authors: Nilay Vaish and Dibakar Gope
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from m5.SimObject import SimObject
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from m5.params import *
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from m5.proxy import *
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class BranchPredictor(SimObject):
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type = 'BranchPredictor'
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cxx_class = 'BPredUnit'
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cxx_header = "cpu/pred/bpred_unit.hh"
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abstract = True
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numThreads = Param.Unsigned(Parent.numThreads, "Number of threads")
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BTBEntries = Param.Unsigned(4096, "Number of BTB entries")
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BTBTagSize = Param.Unsigned(16, "Size of the BTB tags, in bits")
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RASSize = Param.Unsigned(16, "RAS size")
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instShiftAmt = Param.Unsigned(2, "Number of bits to shift instructions by")
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useIndirect = Param.Bool(True, "Use indirect branch predictor")
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indirectHashGHR = Param.Bool(True, "Hash branch predictor GHR")
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indirectHashTargets = Param.Bool(True, "Hash path history targets")
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indirectSets = Param.Unsigned(256, "Cache sets for indirect predictor")
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indirectWays = Param.Unsigned(2, "Ways for indirect predictor")
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indirectTagSize = Param.Unsigned(16, "Indirect target cache tag bits")
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indirectPathLength = Param.Unsigned(3,
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"Previous indirect targets to use for path history")
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class LocalBP(BranchPredictor):
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type = 'LocalBP'
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cxx_class = 'LocalBP'
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cxx_header = "cpu/pred/2bit_local.hh"
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localPredictorSize = Param.Unsigned(2048, "Size of local predictor")
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localCtrBits = Param.Unsigned(2, "Bits per counter")
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class TournamentBP(BranchPredictor):
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type = 'TournamentBP'
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cxx_class = 'TournamentBP'
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cxx_header = "cpu/pred/tournament.hh"
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localPredictorSize = Param.Unsigned(2048, "Size of local predictor")
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localCtrBits = Param.Unsigned(2, "Bits per counter")
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localHistoryTableSize = Param.Unsigned(2048, "size of local history table")
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globalPredictorSize = Param.Unsigned(8192, "Size of global predictor")
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globalCtrBits = Param.Unsigned(2, "Bits per counter")
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choicePredictorSize = Param.Unsigned(8192, "Size of choice predictor")
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choiceCtrBits = Param.Unsigned(2, "Bits of choice counters")
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class BiModeBP(BranchPredictor):
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type = 'BiModeBP'
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cxx_class = 'BiModeBP'
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cxx_header = "cpu/pred/bi_mode.hh"
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globalPredictorSize = Param.Unsigned(8192, "Size of global predictor")
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globalCtrBits = Param.Unsigned(2, "Bits per counter")
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choicePredictorSize = Param.Unsigned(8192, "Size of choice predictor")
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choiceCtrBits = Param.Unsigned(2, "Bits of choice counters")
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class TAGEBase(SimObject):
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type = 'TAGEBase'
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cxx_class = 'TAGEBase'
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cxx_header = "cpu/pred/tage_base.hh"
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numThreads = Param.Unsigned(Parent.numThreads, "Number of threads")
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instShiftAmt = Param.Unsigned(Parent.instShiftAmt,
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"Number of bits to shift instructions by")
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nHistoryTables = Param.Unsigned(7, "Number of history tables")
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minHist = Param.Unsigned(5, "Minimum history size of TAGE")
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maxHist = Param.Unsigned(130, "Maximum history size of TAGE")
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tagTableTagWidths = VectorParam.Unsigned(
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[0, 9, 9, 10, 10, 11, 11, 12], "Tag size in TAGE tag tables")
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logTagTableSizes = VectorParam.Int(
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[13, 9, 9, 9, 9, 9, 9, 9], "Log2 of TAGE table sizes")
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logRatioBiModalHystEntries = Param.Unsigned(2,
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"Log num of prediction entries for a shared hysteresis bit " \
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"for the Bimodal")
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tagTableCounterBits = Param.Unsigned(3, "Number of tag table counter bits")
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tagTableUBits = Param.Unsigned(2, "Number of tag table u bits")
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histBufferSize = Param.Unsigned(2097152,
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"A large number to track all branch histories(2MEntries default)")
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pathHistBits = Param.Unsigned(16, "Path history size")
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logUResetPeriod = Param.Unsigned(18,
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"Log period in number of branches to reset TAGE useful counters")
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numUseAltOnNa = Param.Unsigned(1, "Number of USE_ALT_ON_NA counters")
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useAltOnNaBits = Param.Unsigned(4, "Size of the USE_ALT_ON_NA counter")
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maxNumAlloc = Param.Unsigned(1,
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"Max number of TAGE entries allocted on mispredict")
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# List of enabled TAGE tables. If empty, all are enabled
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noSkip = VectorParam.Bool([], "Vector of enabled TAGE tables")
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speculativeHistUpdate = Param.Bool(True,
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"Use speculative update for histories")
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# TAGE branch predictor as described in https://www.jilp.org/vol8/v8paper1.pdf
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# The default sizes below are for the 8C-TAGE configuration (63.5 Kbits)
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class TAGE(BranchPredictor):
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type = 'TAGE'
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cxx_class = 'TAGE'
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cxx_header = "cpu/pred/tage.hh"
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tage = Param.TAGEBase(TAGEBase(), "Tage object")
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class LTAGE_TAGE(TAGEBase):
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nHistoryTables = 12
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minHist = 4
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maxHist = 640
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tagTableTagWidths = [0, 7, 7, 8, 8, 9, 10, 11, 12, 12, 13, 14, 15]
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logTagTableSizes = [14, 10, 10, 11, 11, 11, 11, 10, 10, 10, 10, 9, 9]
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logUResetPeriod = 19
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class LoopPredictor(SimObject):
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type = 'LoopPredictor'
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cxx_class = 'LoopPredictor'
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cxx_header = 'cpu/pred/loop_predictor.hh'
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logSizeLoopPred = Param.Unsigned(8, "Log size of the loop predictor")
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withLoopBits = Param.Unsigned(7, "Size of the WITHLOOP counter")
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loopTableAgeBits = Param.Unsigned(8, "Number of age bits per loop entry")
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loopTableConfidenceBits = Param.Unsigned(2,
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"Number of confidence bits per loop entry")
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loopTableTagBits = Param.Unsigned(14, "Number of tag bits per loop entry")
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loopTableIterBits = Param.Unsigned(14, "Nuber of iteration bits per loop")
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logLoopTableAssoc = Param.Unsigned(2, "Log loop predictor associativity")
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# Parameters for enabling modifications to the loop predictor
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# They have been copied from TAGE-GSC-IMLI
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# (http://www.irisa.fr/alf/downloads/seznec/TAGE-GSC-IMLI.tar)
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#
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# All of them should be disabled to match the original LTAGE implementation
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# (http://hpca23.cse.tamu.edu/taco/camino/cbp2/cbp-src/realistic-seznec.h)
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# Add speculation
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useSpeculation = Param.Bool(False, "Use speculation")
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# Add hashing for calculating the loop table index
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useHashing = Param.Bool(False, "Use hashing")
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# Add a direction bit to the loop table entries
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useDirectionBit = Param.Bool(False, "Use direction info")
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# If true, use random to decide whether to allocate or not, and only try
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# with one entry
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restrictAllocation = Param.Bool(False,
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"Restrict the allocation conditions")
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initialLoopIter = Param.Unsigned(1, "Initial iteration number")
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initialLoopAge = Param.Unsigned(255, "Initial age value")
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optionalAgeReset = Param.Bool(True,
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"Reset age bits optionally in some cases")
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# LTAGE branch predictor as described in
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# https://www.irisa.fr/caps/people/seznec/L-TAGE.pdf
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# It is basically a TAGE predictor plus a loop predictor
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# The differnt TAGE sizes are updated according to the paper values (256 Kbits)
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class LTAGE(TAGE):
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type = 'LTAGE'
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cxx_class = 'LTAGE'
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cxx_header = "cpu/pred/ltage.hh"
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tage = LTAGE_TAGE()
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loop_predictor = Param.LoopPredictor(LoopPredictor(), "Loop predictor")
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