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Branch predictor

In computer architecture, a branch predictor is the part of a processor that determines whether a branch in the instruction flow of a program is likely to be taken or not. This is called branch prediction. Branch predictors are crucial in today's modern, superscalar processors for achieving high performance. They allow processors to fetch and execute instructions without waiting for a branch to be resolved.

All pipelined processors do branch prediction of some form, because they must guess the address of the next instruction to fetch before the current instruction has been executed. Earlier microprogrammed CPUs did not have to do branch prediction.

Table of contents
1 Trivial Prediction
2 Next Line Prediction
3 Bimodal Branch Prediction
4 Local Branch Prediction
5 Global Branch Prediction
6 Combined Branch Prediction
7 Agree Prediction
8 Overriding Branch Prediction
9 History
10 External Links

Trivial Prediction

The original commercial RISCs, SPARC and MIPS, did trivial branch prediction (always predict not taken) in the sense that they always fetched the next sequential instruction. Only when a branch or jump was evaluated did the instruction fetch pointer get set to a nonsequential address.

Both CPUs evaluated branches in the decode stage and had a single cycle instruction fetch. As a result, the branch target recurrence was two cycles long, and the machine would always fetch the instruction immediately after any taken branch. Both architectures defined branch delay slots in order to utilize these fetched instructions.

Next Line Prediction

Some superscalar processors, (MIPS R8000, Alpha EV6 and EV8), fetched with each line of instructions a pointer to the next line. This next line predictor is not directly comparable to the other predictors listed here, because it handles both the branch target prediction as well as the branch direction prediction.

When a next line predictor points to aligned groups of 2, 4 or 8 instructions, the branch target will usually not be the first instruction fetched, and so the initial instructions fetched are wasted. Assuming for simplicity a uniform distribution of branch targets, 0.5, 1.5, and 3.5 instructions fetched are discarded, respectively.

Since the branch itself will generally not be the last instruction in an aligned group, instructions after the taken branch (or it's delay slot) will be discarded. Once again assuming a uniform distribution of branch instruction placements, 0.5, 1.5, and 3.5 instructions fetched are discarded.

The discarded instructions at the branch and destination lines add up to nearly a complete fetch cycle, even for a single-cycle next-line predictor.

Bimodal Branch Prediction

A bimodal branch predictor has a table of two-bit saturating counters, indexed with the LSBs of the instruction addresses. Unlike the instruction cache, bimodal predictor entries typically do not have tags, and so a particular counter may correspond to two branches, in which case it is likely to be less accurate. Each counter has one of four states:

When a branch is evaluated, the corresponding counter is updated. Branches evaluated as not taken decrement the state towards strongly not taken, and branches evaluated as taken increment the state towards strongly taken. The primary benefit of this two bit saturating counter scheme is that loop closing branches are always predicted taken. A one-bit scheme (like the R8000), mispredicts both the first and last branch of a loop. A two-bit scheme mispredicts just the last branch. Similarly, on heavily branches which only occasionally go one way, a one-bit scheme mispredicts twice for each odd branch, and a two-bit scheme mispredicts once.

On the SPEC'89 benchmarks, very large bimodal predictors saturate at 93.5% correct, once every branch maps to a unique counter.

Because the bimodal counter table is indexed with the instruction address bits, a superscalar processor can split the table into separate SRAMs for each instruction fetched, and fetch a prediction for every instruction in parallel with fetching the instruction, so that the branch prediction is available as soon as the branch is decoded.

Local Branch Prediction

Bimodal branch prediction mispredicts the exit of every loop. For loops which tend to have the same loop count every time (and for many other branches with repetitive behavior), we can do much better.

We can keep two tables in the branch predictor. The local branch history table, indexed by the low-order bits of the branch instruction's address, records the taken/not-taken history of the n most recent executions of each branch.

The other table is a bunch of bimodal counters indexed by the branch history in the first table. To predict a branch, the branch history is looked up, and that history is then used to look up a bimodal counter which makes a prediction.

On the SPEC'89 benchmarks, very large local predictors saturate at 97.1% correct.

Local prediction is hard to make fast because it requires two sequential table lookups for each prediction. A fast implementation would use a separate bimodal counter array for each instruction fetched, so that the second array access can proceed in parallel with instruction fetch. These arrays are not redundant, as each counter is intended to store the behavior of a single branch.

Global Branch Prediction

It turns out that the recent history of other branches is strongly correlated with the behavior of many branches. We can keep a single shift register updated with the recent history of every branch executed, and use this value to index into a table of bimodal counters. This scheme, by itself, is only better than the bimodal scheme for large table sizes, and is never as good as local prediction.

If, instead, we index the table of bimodal counters with the recent history concatenated with a few bits of the branch instruction's address, we get the gselect predictor. Gselect does better than local prediction for small table sizes, and local prediction is only slightly better for table storage larger than 1KB.

We can do slightly better than gselect by XORing the branch instruction address with the global history, rather than concatenating. The result is gshare, which is a little better than gselect for tables larger than 256 bytes.

On the SPEC'89 benchmarks, very large gshare predictors saturate at 96.6% correct, which is just a little worse than large local predictors.

Gselect and gshare are easier to make fast than local prediction, because they require a single table lookup per branch. As with bimodal prediction, the table can be split so that parallel lookups can be made for each instruction fetched, so that the table lookup can proceed in parallel with instruction load.

Combined Branch Prediction

Scott McFarling proposed combined branch prediction in his 1993 paper. Combined branch prediction is about as accurate as local prediction, and almost as fast as global prediction.

Combined branch prediction uses three predictors in parallel: bimodal, gshare, and a bimodal-like predictor to pick which of bimodal or gshare to use on a branch-by-branch basis. The choice predictor is yet another 2-bit up/down saturating counter, in this case the MSB choosing the prediction to use. In this case the counter is updated whenever the bimodal and gshare predictions disagree, to favor whichever predictor was actually right.

On the SPEC'89 benchmarks, such a predictor is about as good as the local predictor.

Another way of combining branch predictors is to have e.g. 3 different branch predictors, and merge their results by a majority vote.

Predictors like gshare use multiple table entries to track the behavior of any particular branch. This multiplication of entries makes it much more likely that two branches will map to the same table entry (a situation called aliasing), which in turn makes it much more likely that prediction accuracy will suffer for those branches. Once you have multiple predictors, it is beneficial to arrange that each predictor will have different aliasing patterns, so that it is more likely that at least one predictor will have no aliasing. Combined predictors with different indexing functions for the different predictors are called gskew predictors, and are analagous to skewed caches used for data and instruction caching.

Agree Prediction

Another technique to reduce destructive aliasing within the pattern history tables is an agree predictor. Some method is used to establish a relatively static prediction for the branch, perhaps a bimodal predictor or hint bits within the branch instruction. Another predictor (e.g. a gskew predictor) makes predictions, but rather than predicting taken/not-taken, the predictor predicts agree/disagree with the base prediction.

The intention is that if branches covered by the gskew predictor tend to be a bit biased in one direction, perhaps 70%/30%, then all those biases can be aligned so that the gskew pattern history table will tend to have more agree entries than disagree entries. This reduces the likelihood that two aliasing branches would best have opposite values in the PHT.

Agree predictors work well with combined predictors, because the combined predictor usually has a bimodal predictor which can be used as the base for the agree predictor. Agree predictors do less well with branches that are not biased in one direction, if that causes the base predictor to give changing predictions. So an agree predictor may work best as part of a three-predictor scheme, with one agree predictor and another non-agree type predictor.

Overriding Branch Prediction

The EV6 and EV8 cores used a fast single-cycle next line predictor to handle the branch target recurrence and provide a simple and fast branch prediction. Because the next line predictor is so inaccurate, and the branch resolution recurrence takes so long, both cores have two-cycle secondary branch predictors which can override the prediction of the next line predictor at the cost of a single lost fetch cycle.

Since a fetch of 4 instructions or more may contain more than one branch, an overriding predictor will sometimes have to predict a next PC which is neither the fall-through nor the earlier predicted next line. The overriding predictor usually extracts the target address from the instruction bytes themselves since they are available by the time the predictor must generate a predicted next fetch address.


Microprogrammed processors took multiple cycles per instruction, and generally did not require branch prediction. The VAX 9000 was both microprogrammed and pipelined, and probably did some branch prediction.

The first commercial RISC processors, MIPS and SPARC, did only trivial "not-taken" branch prediction. Because they used branch delay slots, fetched just one instruction per cycle, and executed in-order, there was no performance loss. Later, the R4000 used the same trivial "not-taken" branch prediction, and lost two cycles to each taken branch because the branch resolution recurrence was four cycles long.

Branch prediction became more important with the introduction of pipelined superscalar processors like the Intel Pentium, DEC Alpha 21064, the MIPS R8000, and the IBM Power series. These processors all relied on one-bit or simple bimodal predictors.

The DEC Alpha EV6 uses a next-line predictor overridden by a combined local predictor and global predictor, where the combining choice is made by a bimodal predictor.

The AMD K8 has a combined bimodal and global predictor, where the combining choice is another bimodal predictor. This processor caches the base and choice bimodal predictor counters in bits of the L2 cache otherwise used for ECC. As a result, it has effectively very large base and choice predictor tables, and parity rather than ECC on instructions in the L2 cache. Parity is just fine, since any instruction suffering a parity error can be invalidated and refetched from memory.

The Alpha EV8 (cancelled late in design) had a minimum branch misprediction penalty of 14 cycles. It was to use a complex but fast next line predictor overridden by a combined bimodal and majority-voting predictor. The majority vote was between the bimodal and two gskew predictors.

External Links

Combining Branch Predictors - McFarling - 1993 - introduces combined predictors. Very good.

Multiple-Block Ahead Branch Predictors - Seznec et al - 1996 - demonstrates prediction accuracy is not impaired by indexing with previous branch address.

Design Tradeoffs for the Alpha EV8 Conditional Branch Predictor - Seznec et al - 2002 - describes the Alpha EV8 branch predictor. This paper does an excellent job discussing how they arrived at their design from various hardware constraints and simulation studies. Very good.

Reconsidering Complex Branch Predictors - Jimenez - 2003 - describes the EV6 and K8 branch predictors, and pipelining considerations.