Measuring cmov vs branch-mov performance
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Comparing the performance of Intel's cmov instruction with a conditional branch + mov pair.

Suppose you want to write the following code inside a performance critical loop:

    if(cond) {
        foo = bar;
    }

where foo is a local variable (of some simple type, like int), and bar is either a local variable, or a simple memory location (such as A[i]). Such a code is likely to be found for example in a Kadane's algorithm implementation.

There are two standard ways for an x86-64 compiler to translate this conditional into Intel assembly, namely a cmov instruction, or a conditional branch paired with a regular mov.

To make this example more concrete I will focus on this particular code:

    int j;
    int res = 0;
    for(j = 0; j < n; ++j) {
        if(A[j]) {
            res = j;
        }
    }

GCC version 4.8.2 emits the following code for the if at -O3 (gas' assembly notation):

    movl    (%rdi,%rcx,4), %r9d
    testl   %r9d, %r9d
    cmovne  %ecx, %eax

Clearly the compiler stores the location of A in %rdi, the value of j in %rcx (%ecx), and res in %rax (%eax).

We may however ask it to forget about the cmov instruction by using the following command line parameters in addition to -O3: -fno-tree-loop-if-convert -fno-tree-loop-if-convert-stores -fno-if-conversion -fno-if-conversion2. Then we will obtain the following assembly:

    movl    (%rdi,%rcx,4), %r9d
    testl   %r9d, %r9d
    je  .L4
    movl    %ecx, %eax
.L4:

To make this example more interesting let's feed the compiler with more data. GCC (and others probably too) implements a mechanism allowing the programmer to specify that a condition will likely/unlikely be true during the runtime. In our case it would look like this (assuming that we are expecting A[j] to be generally false):

    int j;
    int res = 0;
    for(j = 0; j < n; ++j) {
        if(__builtin_expect(A[j], 0)) {
            res = j;
        }
    }

The corresponding GCC output:

    movl    (%rdi,%rcx,4), %r9d
    testl   %r9d, %r9d
    jne .L20
.L14:
    /* Other code */
.L20:
    movl    %ecx, %eax
    jmp .L14

We are of course free to put 1 in the place of 0 whenever we expect A[j] to be true most of the time:

    int j;
    int res = 0;
    for(j = 0; j < n; ++j) {
        if(__builtin_expect(A[j], 1)) {
            res = j;
        }
    }

And the corresponding GCC output (note the speculative movl execution!):

    movl    %eax, %r8d
    movl    (%rdi,%rcx,4), %r10d
    movl    %ecx, %eax
    testl   %r10d, %r10d
    je  .L29
.L24:
    /* Other code */
.L29:
    movl    %r8d, %eax
    jmp .L24

This way we obtain four versions of the program which I will call cmov, branch, branch_0 and branch_1. One might ask why there is no cmov_0 and no cmov_1, but it is due to the fact that in cmov's case the compiler ignored the likely/unlikely hints.

The point of this excercise is to measure their execution speed, but this of course depends on the contents of the A array. So let's fill it with random independent identically distributed zeros and ones, manipulating the probability of one (the probability that the if's condition will be true).

Update 2018:

Thanks to AndreasPK for providing this data.

On an i7-6700k (Skylake) cmov is now faster under all circumstances: Results

While the performance at the extremes looks the same cmov is still faster which becomes obvious when looking at the raw numbers:

0.000000;0.983000;0.412000;0.550000;0.411000
...
1.000000;0.747000;0.951000;0.591000;0.398000

branch_0 comes (very) close for probability zero but was still always slightly slower than cmov in 10 tests I ran.

Original Results

These are the results I obtained on my machine. It is the execution time, so the lower the better: Results

Three interesting facts can be read from this plot:

  • The cmov instruction is generally faster. It is also immune to the probability
  • However the branch version is faster for stable, predictable conditions.
  • The branch versions take approximately p*(1-p) time to execute. The nice parabola-alike looks is approximately the variance of the distribution that A was sampled from.

The "visual proof" for the third fact: Results with a parabola

To conclude, GCC emits cmov by default, and it seems like a reasonable choice, at least on my Intel Core i5. However, as noted before, it is not the optimal solution for stable, predictable conditions.