A%20256%20Kbits%20L-TAGE%20branch%20predictor

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A 256 Kbits L-TAGE branch predictor

• André Seznec
• IRISA/INRIA/HIPEAC

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• Directly derived from
• A case for (partially) tagged branch
  predictors,
• A. Seznec and P. Michaud JILP Feb. 2006
• Tricks
• Loop predictor
• Kernel/user histories

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TAGE TAgged GEometric history length predictors
The genesis
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Back around 2003

• 2bcgskew was state-of-the-art, but
• but was lagging behind neural inspired
  predictors on a few benchmarks
• Just wanted to get best of both behaviors and
  maintain
• Reasonable implementation cost
• Use only global history
• Medium number of tables
• In-time response

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The basis A Multiple length global history
predictor
TO
T1
T2
?
L(0)
T3
L(1)
L(2)
T4
L(3)
L(4)
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GEometric History Length predictor
The set of history lengths forms a geometric
series
Capture correlation on very long histories
0, 2, 4, 8, 16, 32, 64, 128
most of the storage for short history !!
What is important L(i)-L(i-1) is drastically
increasing
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Combining multiple predictions ?

• Classical solution
• Use of a meta predictor
• wasting storage !?!
• chosing among 5 or 10 predictions ??
• Neural inspired predictors, Jimenez and Lin 2001
• Use an adder tree instead of a meta-predictor
• Partial matching
• Use tagged tables and the longest matching
  history
• Chen et al 96, Michaud 2005

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CBP-1 (2004) OGEHL Final computation through a
sum
L(0)
PredictionSign
12 components 3.670 misp/KI
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TAGEGeometric history length PPM-like
optimized update policy
Tagless base predictor
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Prediction computation

• General case
• Longest matching component provides the
  prediction
• Special case
• Many mispredictions on newly allocated entries
  weak Ctr
• On many applications, Altpred more accurate than
  Pred
• Property dynamically monitored through a single
  4-bit counter

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TAGE update policy

• General principle
• Minimize the footprint of the prediction.
• Just update the longest history matching
  component and allocate at most one entry on
  mispredictions

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A tagged table entry

• Ctr 3-bit prediction counter
• U 2-bit useful counter
• Was the entry recently useful ?
• Tag partial tag

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Updating the U counter

• If (Altpred ? Pred) then
• Pred taken U U 1
• Pred ? taken U U - 1

• Graceful aging
• Periodic shift of all U counters
• implemented through the reset of a single bit

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Allocating a new entry on a misprediction

• Find a single useless entry with a longer
  history
• Priviledge the smallest possible history
• To minimize footprint
• But not too much
• To avoid ping-pong phenomena
• Initialize Ctr as weak and U as zero

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Improve the global history

• Address conditional branch history
• path confusion on short histories ?
• Address path
• Direct hashing leads to path confusion ?
• Represent all branches in branch history
• Use also path history ( 1 bit per branch, limited
  to 16 bits)

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Design tradeoff for CBP2 (1)

• 13 components
• Bring the best accuracy on distributed traces
• 8 components not very far !
• History length
• Min4 , Max 640
• Could use any Min in 2,6 and any Max in 300,
  2000

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Design tradeoff for CBP2 (2)

• Tag width tradeoff
• (destructive) false match is better tolerated on
  shorter history
• 7 bits on T1 to 15 bits on T12
• Tuning the number of table entries
• Smaller number for very long histories
• Smaller number for very short histories

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Adding a loop predictor

• The loop predictor captures the number of
  iterations of a loop
• When successively encounters 4 times the same
  number of iterations, the loop predictor
  provides the prediction.
• Advantages
• Very reliable
• Small storage budget 256 52-bit entries
• Complexity ?
• Might be difficult to manage speculative
  iteration numbers on deep pipelines

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Using a kernel history and a user history

• Traces mix user and kernel activities
• Kernel activity after exception
• Global history pollution
• Solution use two separate global histories
• User history is updated only in user mode
• Kernel history is updated in both modes

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L-TAGE submission accuracy (distributed traces)
3.314 misp/KI
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Reducing L-TAGE complexity

• Included 241,5 Kbits TAGE predictor
• 3.368 misp/KI
• Loop predictor beneficial only on gzip
• Might not be worth the extra complexity

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Using less tables

• 8 components 256 Kbits TAGE predictor
• 3.446 misp/KI

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TAGE prediction computation time ?

• 3 successive steps
• Index computation
• Table read
• Partial match multiplexor
• Does not fit on a single cycle
• But can be ahead pipelined !

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Ahead pipelining a global history branch
predictor (principle)

• Initiate branch prediction X1 cycles in advance
  to provide the prediction in time
• Use information available
• X-block ahead instruction address
• X-block ahead history
• To ensure accuracy
• Use intermediate path information

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Practice
A
C
B
bc
Ahead pipelined TAGE 4// prediction computations
Ha A
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3-branch ahead pipelined 8 component 256 Kbits
TAGE
3.552 misp/KI
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A final case for the Geometric History Length
predictors

• delivers state-of-the-art accuracy
• uses only global information
• Very long history 300 bits !!
• can be ahead pipelined
• many effective design points
• OGEHL or TAGE ?
• Nb of tables, history lengths

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The End ?