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Loop Unrolling Transformation: Difference between revisions
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→Partial and Full Loop Unrolling
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Loop unrolling can be either partial or full, depending on how many iterations are combined into a single loop body. | 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. | ||
== Loop Unrolling in C/C++ Compilers == | == Loop Unrolling in C/C++ Compilers == | ||
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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. | 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. | ||
**Generic Pragmas (Applicable across multiple compilers) | **Generic Pragmas (Applicable across multiple compilers) | ||
* `#pragma unroll(n)` — Requests the compiler to unroll the loop by a factor of `n`. | * `#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 nounroll` — Explicitly disables unrolling for the annotated loop. | ||
**Clang Pragmas | **Clang Pragmas | ||
* `#pragma clang loop unroll(enable)` — Enables loop unrolling. | * `#pragma clang loop unroll(enable)` — Enables loop unrolling. | ||
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* `#pragma clang loop unroll_count(4)` — Specifies an unroll factor of 4. | * `#pragma clang loop unroll_count(4)` — Specifies an unroll factor of 4. | ||
**GCC Pragmas | **GCC Pragmas | ||
* `#pragma GCC unroll` — Enables automatic unrolling. | * `#pragma GCC unroll` — Enables automatic unrolling. | ||
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* `#pragma GCC unroll(UNROLLCOUNT)` — Requests a specific unroll factor. | * `#pragma GCC unroll(UNROLLCOUNT)` — Requests a specific unroll factor. | ||
**OpenMP Pragmas | **OpenMP Pragmas | ||
OpenMP 5.0 introduced loop unrolling pragmas to allow explicit unrolling in parallel programs: | OpenMP 5.0 introduced loop unrolling pragmas to allow explicit unrolling in parallel programs: | ||