1. The O-GEHL branch predictor
Optimized GEometric History Length
André Seznec
IRISA/INRIA/HIPEAC

2. Branch prediction is still an issue
Long pipelines
Multiple instruction per cycle
Any gain in branch prediction accuracy results in:
Performance gain
Power consumption gain

3. What must be predicted:
Directions and targets:
Indirect branch target
Conditional branch direction
This presentation:
Only conditional branch direction

4. Conditional branch predictors
Two main sources of information:
Local history
the past behavior of this particular branch
Global history
the (recent) past behavior of all branches

5. Speculative history must be managed !?
Global history:
Append a bit on a single history register
Use of a circular buffer and just a pointer to speculatively manage the history
Local history:
table of histories (unspeculatively updated)
must maintain a speculative history per inflight branch:
Associative search, etc ?!?

6. From my experience with EV8 team
Designers hate
maintaining
speculative local history

7. “Classic” stuff with the OGEHL predictor 
Global history based:
Yeh and Patt 91, Pan and So 91
Multiple history lengths to index multiple tables
McFarling 93, Evers et al. 96, EV8 predictor

8. Selecting between multiple predictions
Classic solution:
Use of a meta predictor
“wasting” storage !?!
chosing among 5 or 10 predictions ??
Neural inspired predictors:
Use an adder tree instead of a meta-predictor
Vintan and Iridon 99, Jimènez and Lin 01
Let’s use the adder tree

9. Perceptron predictor
One weight per history bit ∑ X
Sign=prediction

10. What makes such predictor working ?
Use of signed saturated counters:
8-bit on perceptron predictors
Partial update policy:
Update all the counters on misprediction
Update all the counters when sum absolute value is under a threshold
For perceptron predictors:
Θ= 2.14 N

11. Perceptron predictors: strong points and shortcomings
Effective solution for selecting the prediction
Hardware cost scales linearly with the history length !
Shortcomings:
High number of adders
Long latency
Good accuracy, but no better than conventional hybrid predictors
Hardware cost scales linearly with the history length ?

12. Multiple history length predictor∑
L(4)
L(3)
L(2)
L(1)
L(0) TO T1 T2 T3 T4
Multiple history length predictor
Prediction=Sign

13. GEometric History Length predictor
The set of history lengths forms a geometric series
{0, 2, 4, 8, 16, 32, 64, 128}
What is important: L(i)-L(i-1) is drastically increasing
Spends most of the storage for short history !!

14. Counter width on O-GEHL predictors
8 bits are just overkilling 
4 bits are sufficient 
Mixing 5 bits for short histories and 4 bits for long histories is slightly better 
3 bits are not so bad !!

15. Dynamic update threshold fitting
Reasonable fixed threshold= Number of tables
On an O-GEHL predictor, best threshold depends on
the application 
the predictor size 
the counter width 
By chance, on most applications, for the best fixed threshold,
updates on mispredictions ≈ updates on correct predictions
Monitor the difference
and adapt the update threshold

16. Adaptative history length fitting (inspired by Juan et al 98)
(½ applications: L(7) < 50) ≠
(½ applications: L(7) > 150)
Let us adapt some history lengths to the behavior of each application
8 tables:
T2: L(2) and L(8)
T4: L(4) and L(9)
T6: L(6) and L(10)

17. Adaptative history length fitting (2)
Intuition:
if high degree of conflicts on T7, stick with short history
Implementation:
monitoring of aliasing on updates on T7 through a tag bit and a counter
Simple is sufficient:
Flipping from short to long histories and vice-versa

18. TO T1 T2
L(0) ∑ T3
L(1) or L(5)
L(2) T4
L(3) or L(6)
L(4)
Tag bits

19. What is 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)

20. Hashing 200+ bits for indexing !!
Need to compute 11 bits indexes :
Full hashing is unrealistic
Just regularly pick at most 33 bits in:
address+branch history +path history
A single 3-entry exclusive-OR stage

21. Evaluation framework 1st Championship Branch Prediction traces:
20 traces including system activity
Floating point apps : loop dominated
Integer apps
Multimedia apps
Server workload apps: very large footprint

22. CBP A single rule: The storage budget must fit 64K + 256 bits.
Rule artefacts
Don’t care about implementability
Initialize the predictor with what is convenient
Adapt the configuration to each benchmark, but don’t care about transition between applications

23. Configuration presented for Championship Branch Prediction
8 tables:
2 Kentries except T1, 1Kentries
5 bit counters for T0 and T1, 4 bit counters otherwise
1 Kbits of one bit tags associated with T7
10K + 5K + 6x8K + 1K = 64K
L(1) =3 and L(10)= 200
{0,3,5,8,12,19,31,49,75,125,200}

24. A case for the OGEHL predictor
2nd at CBP: 2.82 misp/KI
Best practice award:
The predictor the closest to a possible hardware implementation
Chaining simulations: 2.84 misp/KI
The winner: 4.34 misp/KI
(but respecting the rule is respecting the rule )

25. A case for the OGEHL predictor (2)
High accuracy
Half size 32Kbits (3,150): 3.41 misp/KI
better than any “implementable” 64Kbits predictor before CBP
Robustness to variations of history lengths choices:
L(1) in [2,6], L(10) in [125,300]
misp. rate < 2.96 misp/KI
Geometric series: not a bad formula !!
best geometric L(1)=3, L(10)=223, misp/KI
best overall {0, 2, 4, 9, 12, 18, 31, 54, 114, 145, 266} misp/KI

26. A case for the OGEHL predictor (3)
Reduce counter width by 1 bit: 49 Kbits
would have been a finalist at CBP (3.09) 
64 Kbits 4 components OGEHL predictor
would have been a finalist at CBP (3.02) 
50 Kbits 4 components OGEHL predictor (3-bit)
would have been a finalist at CBP (3.21) 
768 Kbits 12 components OGEHL predictor
2.25 misp/KI

27. Prediction computation time
3 components:
Index computation
Counter read
Adder tree
Does not fit on a single cycle:
But may be ahead pipelined !

28. Ahead pipelining a global history branch predictor (principle)
Initiate branch prediction X+1 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

29. 8 // prediction computations
Practice A B C D
bcd
Ahead OGEHL:
8 // prediction computations Ha A

30. Ahead Pipelined 64 Kbits OGEHL
3-block: 2.94 misp/KI
4-block: 2.99 misp/KI
5-block: 3.04 misp/KI
Not such a huge accuracy loss 

31. A final case for the O-GEHL predictor
delivers state-of-the-art accuracy
uses only global information
can be ahead pipelined
many effective design points
Nb of tables, counter width, ..
prediction computation logic complexity is low
(compared with concurrent predictors)
(The End)