程序代写代做代考 compiler Microsoft PowerPoint – 6_BranchPred.ppt

Microsoft PowerPoint – 6_BranchPred.ppt

CS 6290
Branch Prediction

Control Dependencies

• Branches are very frequent
– Approx. 20% of all instructions

• Can not wait until we know where it goes
– Long pipelines

•Branch outcome known after B cycles
•No scheduling past the branch until outcome known

– Superscalars (e.g., 4-way)
•Branch every cycle or so!
•One cycle of work, then bubbles for ~B cycles?

Surviving Branches: Prediction

• Predict Branches
– And predict them well!

• Fetch, decode, etc. on the predicted path
– Option 1: No execute until branch resovled
– Option 2: Execute anyway (speculation)

• Recover from mispredictions
– Restart fetch from correct path

Branch Prediction

• Need to know two things
– Whether the branch is taken or not (direction)
– The target address if it is taken (target)

• Direct jumps, Function calls
– Direction known (always taken), target easy to compute

• Conditional Branches (typically PC-relative)
– Direction difficult to predict, target easy to compute

• Indirect jumps, function returns
– Direction known (always taken), target difficult

Branch Prediction: Direction

• Needed for conditional branches
– Most branches are of this type

• Many, many kinds of predictors for this
– Static: fixed rule, or compiler annotation

(e.g. “BEQL” is “branch if equal likely”)
– Dynamic: hardware prediction

• Dynamic prediction usually history-based
– Example: predict direction is the same

as the last time this branch was executed

Static Prediction

• Always predict NT
– easy to implement
– 30-40% accuracy … not so good

• Always predict T
– 60-70% accuracy

• BTFNT
– loops usually have a few iterations, so this is like

always predicting that the loop is taken
– don’t know target until decode

One-Bit Branch Predictor

K bits of branch
instruction address

Index

Branch history
table of 2^K entries,
1 bit per entry

Use this entry to
predict this branch:

0: predict not taken
1: predict taken

When branch direction resolved,
go back into the table and
update entry: 0 if not taken, 1 if taken

One-Bit Branch Predictor (cont’d)

0xDC08: for(i=0; i < 100000; i++) { 0xDC44: if( ( i % 100) == 0 ) tick( ); 0xDC50: if( (i & 1) == 1) odd( ); } T N The Bit Is Not Enough! • Example: short loop (8 iterations) – Taken 7 times, then not taken once – Not-taken mispredicted (was taken previously) • Execute the same loop again – First always mispredicted (previous outcome was not taken) – Then 6 predicted correctly – Then last one mispredicted again • Each fluke/anomaly in a stable pattern results in two mispredicts per loop Examples DC08: TTTTTTTTTTT ... TTTTTTTTTTNTTTTTTTTT … 100,000 iterations How often is branch outcome != previous outcome? 2 / 100,000 TN NT DC44: TTTTT ... TNTTTTT … TNTTTTT … 2 / 100 DC50: TNTNTNTNTNTNTNTNTNTNTNTNTNTNT … 2 / 2 99.998% Prediction Rate 98.0% 0.0%0.0% Two Bits are Better Than One 0 1 FSM for Last-Outcome Prediction 0 1 2 3 FSM for 2bC (2-bit Counter) Predict NT Predict T Transistion on T outcome Transistion on NT outcome Example 2 T 3 T 3 T …3 N N 1 T 00 T 1 T T T T … T 1 1 1 1 T 1 T …1 0 T 1 T 2 T 3 T 3 T … 3 T Initial Training/Warm-up1bC: 2bC: Only 1 Mispredict per N branches now! DC08: 99.999% DC04: 99.0% Still Not Good Enough We can live with these These are good This is bad! Importance of Branches • 98% 99% – Who cares? – Actually, it’s 2% misprediction rate 1% – That’s a halving of the number of mispredictions • So what? – If misp rate equals 50%, and 1 in 5 insts is a branch, then number of useful instructions that we can fetch is: 5*(1 + ½ + (½)2 + (½)3 + … ) = 10 – If we halve the miss rate down to 25%: 5*(1 + ¾ + (¾)2 + (¾)3 + … ) = 20 – Halving the miss rate doubles the number of useful instructions that we can try to extract ILP from How about the Branch at 0xdc50? • 1bc and 2bc don’t do too well (50% at best) • But it’s still obviously predictable • Why? – It has a repeating pattern: (NT)* – How about other patterns? (TTNTN)* • Use branch correlation – The outcome of a branch is often related to previous outcome(s) Idea: Track the History of a Branch PC Previous Outcome 1 Counter if prev=0 3 0 Counter if prev=1 1 3 3 prev = 1 3 0 prediction = N prev = 0 3 0 prediction = T prev = 1 3 0 prediction = N prev = 0 3 0 prediction = T prev = 1 3 prediction = T3 prev = 1 3 prediction = T3 prev = 1 3 prediction = T2 prev = 0 3 prediction = T2 Deeper History Covers More Patterns • What pattern has this branch predictor entry learned? PC 0 310 1 3 1 0 02 2 Last 3 Outcomes Counter if prev=000 Counter if prev=001 Counter if prev=010 Counter if prev=111 001 1; 011 0; 110 0; 100 1 00110011001… (0011)* Global vs. Local Branch History • Local Behavior – What is the predicted direction of Branch A given the outcomes of previous instances of Branch A? • Global Behavior – What is the predicted direction of Branch Z given the outcomes of all* previous branches A, B, …, X and Y? * number of previous branches tracked limited by the history length Why Global Correlations Exist • Example: related branch conditions p = findNode(foo); if ( p is parent ) do something; do other stuff; /* may contain more branches */ if ( p is a child ) do something else; Outcome of second branch is always opposite of the first branch A: B: Other Global Correlations • Testing same/similar conditions – code might test for NULL before a function call, and the function might test for NULL again – in some cases it may be faster to recompute a condition rather than save a previous computation in memory and re-load it – partial correlations: one branch could test for cond1, and another branch could test for cond1 && cond2 (if cond1 is false, then the second branch can be predicted as false) – multiple correlations: one branch tests cond1, a second tests cond2, and a third tests cond1 ⊕ cond2 (which can always be predicted if the first two branches are known). Tournament Predictors • No predictor is clearly the best – Different branches exhibit different behaviors •Some “constant”, some global, some local • Idea: Let’s have a predictor to predict which predictor will predict better ☺ Tournament Hybrid Predictors Pred0 Pred1 Meta- Predictor Final Prediction table of 2-/3-bit counters --- Dec Inc --- Meta Update Pred1Pred0 If meta-counter MSB = 0, use pred0 else use pred1 Common Combinations • Global history + Local history • “easy” branches + global history – 2bC and gshare • short history + long history • Many types of behaviors, many combinations Direction Predictor Accuracy Target Address Prediction • Branch Target Buffer – IF stage: need to know fetch addr every cycle – Need target address one cycle after fetching a branch – For some branches (e.g., indirect) target known only after EX stage, which is way too late – Even easily-computed branch targets need to wait until instruction decoded and direction predicted in ID stage (still at least one cycle too late) – So, we have a quick-and-dirty predictor for the target that only needs the address of the branch instruction Branch Target Buffer • BTB indexed by instruction address • We don’t even know if it is a branch! • If address matches a BTB entry, it is predicted to be a branch • BTB entry tells whether it is taken (direction) and where it goes if taken • BTB takes only the instruction address, so while we fetch one instruction in the IF stage we are predicting where to fetch the next one from Direction prediction can be factored out into separate table Branch Target Buffer Return Address Stack (RAS) • Function returns are frequent, yet – Address is difficult to compute (have to wait until EX stage done to know it) – Address difficult to predict with BTB (function can be called from multiple places) • But return address is actually easy to predict – It is the address after the last call instruction that we haven’t returned from yet – Hence the Return Address Stack Return Address Stack (RAS) • Call pushes return address into the RAS • When a return instruction decoded, pop the predicted return address from RAS • Accurate prediction even w/ small RAS Example 1: Alpha 21264 • Hybrid predictor – combines local history and global history components with a meta-predictor Example 2: Pentium-M • Also hybrid, but uses tag-based selection mechanism Pentium-M (cont’d) • Local component also has support for loops – accurately predict branches of the form (TkN)* Pentium-M (cont’d) • Special target prediction for indirect branches – common in object-oriented code (vtables) – assumes correlation with global history