Loop Unrolling Transformation: Difference between revisions

Loop unrolling can be either partial or full, depending on how many iterations are combined into a single loop body.  

 

* **Partial Unrolling:** This technique reduces the number of iterations by a factor of N, known as the unroll factor. For example, with an unroll factor of 4, a loop that originally runs 16 times would now run only 4 times, processing 4 iterations' worth of data in each pass. The remaining iterations (if the iteration count is not perfectly divisible by the unroll factor) are handled in a separate, smaller loop known as a cleanup loop. Partial unrolling balances reduced control overhead with manageable code size.

 

* **Full Unrolling:** In full unrolling, the loop is eliminated entirely, and each iteration is explicitly written out as a separate block of code. This maximizes reduction in loop overhead and allows for aggressive compiler optimizations, such as instruction reordering and parallelism. Full unrolling is typically feasible only for small, fixed-size loops where the number of iterations is known at compile time. While this can lead to significant speed improvements, it also increases code size (code bloat), which can negatively impact instruction cache performance in larger programs.

Most modern C/C++ compilers apply automatic loop unrolling when aggressive optimization levels (such as `-O2` or `-O3`) are enabled. The decision to unroll a loop depends on factors such as loop trip count, loop body complexity, and potential performance gains. Compilers analyze loops to identify cases where unrolling reduces overhead or exposes further optimization opportunities, such as vectorization.

 

In addition to automatic unrolling, developers can explicitly influence unrolling behavior through compiler-specific pragmas. These pragmas allow developers to:

 

- Force a specific unroll factor.

 

Compiler pragmas for unrolling provide fine-grained control over how loops are transformed, which is useful when compiler heuristics do not align with application-specific performance goals. For example, manually unrolling cache-sensitive loops can improve data locality, while avoiding unrolling in some cases can reduce code bloat.

Pragmas are compiler directives that influence how a compiler processes specific sections of code, such as loops. They offer direct control over transformations like loop unrolling, bypassing the compiler's default heuristics. This allows developers to optimize for performance or code size, depending on the application requirements. Below are pragma options available for different compilers.

* `#pragma unroll(n)` — Requests the compiler to unroll the loop by a factor of `n`.

* `#pragma nounroll` — Explicitly disables unrolling for the annotated loop.

* `#pragma clang loop unroll(enable)` — Enables loop unrolling.

* `#pragma clang loop unroll(disable)` — Disables loop unrolling.

* `#pragma clang loop unroll(full)` — Requests full unrolling of the loop.

* `#pragma clang loop unroll_count(4)` — Specifies an unroll factor of 4.

* `#pragma GCC unroll` — Enables automatic unrolling.

 

 

 

* `#pragma omp unroll` — Enables unrolling with default heuristics.

* `#pragma omp unroll full` — Requests full unrolling.

* `#pragma omp unroll partial` — Enables partial unrolling.

* `#pragma omp unroll partial(3)` — Specifies an unroll factor of 3.

 

|'''Unroll factor''' - divide iteration count & multiply iterating variable. If equal to total number of iterations, loop-construct will be removed from code. If not integer divisor of total number of iterations, additional loop processing last iterations will be added