Is two statements in a single loop faster than a statement per loop?

user_10778337 0
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Or is it the same in terms of performance?

For example, which is faster?

int a = 1, b = 2;
for (int i = 0; i < 10; ++i) {
    a = a + 1;
    b = b + 1;
}

or

for (int i = 0; i < 10; ++i) {
    a = a + 1;
}
for (int i = 0; i < 10; ++i) {
    b = b + 1;
}

Note: I changed my examples, given a lot of people seem hung up on the statements inside them rather than the purpose of my question.

c++ performance
3 Answers

Both of your examples do nothing at all and most compilers will optimize them both to the same thing -- nothing at all.

Update: Your two new examples are obviously equivalent. If any compiler generated better code for one than the other, then it's a poor quality compiler and you should just use a better compiler.

user_7212690

As people have pointed out, the compiler will optimize regardless of which way I go with but it really depends on what statements are inside the loop(s).

user_107783370

The performance depends on the contents of the loops.

Let's decompose the for loop. A for loop is comprised of:

  1. Initialization
  2. Comparison
  3. Incrementing
  4. Content (statements)
  5. Branching

Let us define a comparison as a compare instruction (to set the processor status bits) and a branch (to take advantage of the processor status bits).

Processors are at their happiest when they are executing data instructions. The processor manipulates the data, then processes the next instruction in the pipeline (cache).

The processors don't like sections 2) Comparison and 5) Branching (to the top of the loop). Branching means that the processor has stop processing data and execute logic to determine if the instruction cache needs to be replaced or not. This time could be spent processing data instructions.

The goal to optimizing a for loop is to reduce the branching. The secondary one is to optimize the data cache / memory accesses. A common optimization technique is loop unrolling, or basically placing more statements inside the for loop. As a measurement, you can take the overhead of the for loop and divide by the quantity of statements inside the loop.

According to the above information, your first loop (with both assignment statements) would be more efficient, since there are more data instructions per loop; less overhead overall.

Edit 1: The Parallel Environment
However, your second example may be faster. The compiler could set up both loops to run in parallel (either through instructions or actual parallel tasks). Since both loops are independent, they can be run at the same time or split between CPU cores. Processors have instructions that can perform common operations on multiple memory locations. Your first example, makes this a little more difficult because it requires more analyzation from the compiler. Since the loops on the second example are simpler, the compiler's analyzation is also simpler.

Also, the quantity of iterations also plays a factor. For small quantities, the loops should perform the same or have negligible differences. For large quantities of iterations, there may be some timing differences.

In summary: PROFILE. BENCHMARK. The only true answer depends on measurements. They may vary depending on the applications being run at the same time, the amount of memory (both RAM and hard drive), the quantity of CPU cores and other items. Profile and Benchmark on your system. Repeat on other systems.

user_2250740
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