1. TAGE-SC-L Branch Predictors
André Seznec
INRIA/IRISA

2. The TAGE-SC-L branch predictor Sorry, nothing really new ..
TAGE, JILP 2006
Considered as state-of-the-art global history predictor
Can be augmented with small adjunct predictors
Loop predictor: CBP-2 (2006)
Statistical Corrector + Loop Predictor,
Global history CBP-3 (2011)
Local history Micro 2011

3. Optimized all parameters
Number, size, width of the tables
Types of the histories for the statistical components
All that for decreasing the misprediction number by 3% !!

4. Global, local, skeleton histories
(Main)
TAGE
Predictor
Stat.
Cor.
Prediction + Confidence
Loop Predictor
PPC +Global history
Global, local, skeleton histories

5. TAGE: multiple tables, global history 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 !!

6. TAGE: Tagged and prediction by the longest history matching entrypc
h[0:L1]
ctr u
tag =?
prediction
h[0:L2]
h[0:L3] 1
Tagless base
predictor

7. =? 1
Hit
Altpred
Pred
Miss

8. 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 4-bit counters

9. A tagged table entry Ctr: 3-bit prediction counter U: 2-bit counters
Was the entry recently useful ?
Tag: partial tag
Tag
Ctr U

10. Allocate entries on mispredictions
Allocate entries in longer history length tables
On tables with U unset
Set Ctr to Weak and U to 0
Limited storage budget:
Allocate 2 entries for 256Kbits
Allocate 1 or 2 for 32Kbits
UNLIMITED STORAGE BUDGET:
multiple entries allocated in different tables

11. Managing the (U)seful counter
Increment when avoids a misprediction
(Pred = taken) & (Alt ≠ taken)
256K: Global decrement if « difficult » to allocate
32K: Probabilistic decrement when conflict
Unlimited: don’t care

12. Adjunct predictors
TAGE tracks strong correlation with the global branch history
Small adjunct predictors to capture some missed correlation:
Loop predictor
Statistical Corrector

13. The loop predictor Predict loop with constant number of iterations:
16/32 entries
less than 5 bytes per entry
Capture loops with long bodies and/or irregular internal branches
S: 1.2 %  M: 1 %  U:0.4% 
Good tradeoff for the Championship
Implementation: Not that great

14. The Statistical Corrector predictor
Branches with poor correlation with global history:
Sometimes better predicted by a single wide PC indexed counter than by TAGE
More generally, track cases such that:
« In this case (PC, history, prediction),
TAGE is likely (>50 %) to mispredict »

15. Small predictor: very limited budget for the SC predictor
Just track the statistically PC biased branches
« TAGE predicts this direction on this branch, but in most cases this was wrong »
The corrector filter:
A small partially tagged associative table
1.5 % misp. reduction:
Much simpler than a loop predictor

16. Medium predictor « Statistically » correlated branches:
Not strongly correlated with the global history, but exhibit a bias
better predicted by averaging than tags
neural  tags
Branches correlated with local history,
but irregular global history pattern (on other branches)
TAGE does not learn the pattern

17. MultiGehl Statistical Correlator Predictor+
H + LH PC
Pred
Gehl-like
Prediction + ctr value
TAGE
Stat.
Corr. H PC
Local hist.

18. Why does it work The bias table indexed with PC+TAGE output:
Correct (most of the time)
High counter value
Dominates, not many updates
Wrong
Other counters can be trained
Correlation (if it exists) can be captured

19. MultiGehl Statistical Correlator Predictor for the Championship
+ RAS associated history
+ 2 different local histories
+ simple choser
6.8 % misp reduction
TAGE H PC
Stat.
Corr.
Prediction + ctr value
Local hist.

20. « Realistic » 256 Kbits TAGE-SC-L
« Only »
12 equal size TAGE tables +
(local hist., global hist.) 4-tables SC
+ loop predictor
No history tuning
Only 2.8 % extra mispredictions

21. SC for Unlimited predictor
GEHL based SC predictor:
Use any form of history information
Very long global
Mutiple local
« Skeleton » global history
ignore some branches
Recycle old ideas from the MAC-RHSP predictor (2004)

22. SC for unlimited predictor
460 predictor tables + 10 choser tables
Globally about 20 % less misp. than TAGE alone
If one removes only :
The bias: 1.6 % for a single table
All global history components: 3.7 %
All local history components: 3.9 %
The choser: 3.2 %

23. Conclusion TAGE-SC-L fits (nearly) all storage sizes
32Kbits ≈ 64Kbits CBP1 champion on CBP1 traces
256Kbits ≈ 512Kbits CBP3 champion on CBP4 traces
Unlimited predictor:
poTAGE-SC does better