March 21, 2018

Branch By Boolean

Once upon a time, all programming was for performance. With computer power at a premium, every instruction was a cost. Oddly, the cost of branching (acting differently based on a condition) has got both more and less expensive. Branches are evaluated more quickly now, but improvements in branch prediction (see below) mean branches can be more costly relative to the branchless option. Modern processors are in some ways more similar to the original supercomputers than ever, in particular, their use of vector operations. In this post we talk a bit about what branch prediction means and show a couple of tricks which can be quite useful in code in important loops.

What is Branch Prediction?

Branch prediction refers to the ability of the processor to predict (aha!) which branch is likely, and to get ready to take it. This can happen before the condition is actually evaluated. Once the condition has been checked, if the guess was correct, the operation stream continues, but if it was wrong the incorrect instructions in the queue must be dumped and the correct instructions for the actual branch assembled. This can sometimes be quite costly. Some systems instead execute both possible branches, and throw away the unneeded result, which can halve their possible throughput.

Generally branch predictors are dumb. The commonest option is to assume whatever track was taken previously will be taken again. This is great when you have one rare case (for example, an error condition) and a common one. Sometimes the predictor can 'understand' simple alternation (option 1, then option 2, then option 1...) or similar patterns if they are 'obvious enough'.

How much does it cost, really?

The costs of branch misprediction vary widely, depending on hardware, vectorisation, surrounding code etc. Most profiling tools will give you a miss rate, and reducing this in regularly repeated pieces of code can be worthwhile. A simple demo of branch misses is given here. I have tried to make all paths as similar as possible. The final print statement ensures that the total is used so the loop cannot be simply optimised away.

On my machine, the example compiled without optimisation takes about 0.8 seconds with compile-time option -DBR_3, i.e. the maximum possible number of addition operations, and the case which would take the longest if there was nothing more than simple looping and addition in play. Options 1 and 2 both take about 1 second, and the option with half true, half false, just over 0.8 seconds. This suggests something like the 'same as last time' prediction occuring.

Avoiding Branches

When it does matter, there are several ways to avoid true branches and greatly improve performance in a piece of code. Always profile first, though, to be sure this piece warrants improving.

A Simple Rejig

The first thing to consider is whether a simple rewrite of the code can eliminate a branch, or improve its prediction. Many branch predictors are quite dumb and assume whatever branch was taken the previous iteration will be taken again. If you can rewrite to ensure longer 'runs' of one branch, this may help. The previous section showed one example where this can be quite dramatic.

Do More to Do Less

Sometimes it may even be more effective to do more work, but without a condition, rather than check if the work needs to be done. A trivial example is something like

  DO i = 0, 10000
    IF (B[i] /= 0) A = A + B[i]

where the check is redundant because if B[i] is zero, the addition does nothing.

Function Pointers

Another useful trick is to use function pointers (or named functions), as discussed in this previous Soup. Rather than putting an 'if' into a vital loop, first work out which function needs to be called and then call it. As given in the previous post, we can replace

  DO i = 0, 10000
    IF (condition) function_1()
    ELSE IF (condition) function_2()
    ELSE IF (condition) function_3()


  IF (condition) ptr = function_1
  ELSE IF (condition) ptr = function_2
  ELSE IF (condition) ptr = function_3

  DO i = 0, 10000

As usual, this may or may not help: in some languages function pointers are slow themselves (not C or Fortran though, but e.g. std::function in C++ can be), and sometimes the called function is already complex enough to break any vectorisation or similar optimisations.

Boolean Branch

One particularly sneaky one is the Boolean Branch, most useful in languages which equate 'True' with 1 and False with '0', but still viable with integers otherwise. The trick is to note that

IF condition THEN
  result = value1
  result = value2

is the same as

flag = condition !Flag may be an integer; in C it can be Boolean
result = value1*flag + value2*(1 - flag)

The conditional assignment in the first case is replaced with two simple assignments. This may or may not be faster! Profiling is essential to find out. It is more likely to pay off in a case where the two options alternate, especially when this is irregular, so the branch prediction fails regularly.

- No comments Not publicly viewable

Add a comment

You are not allowed to comment on this entry as it has restricted commenting permissions.


March 2018

Mo Tu We Th Fr Sa Su
Feb |  Today  | Apr
         1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 31   

Search this blog



Blog archive

Not signed in
Sign in

Powered by BlogBuilder