Loop Optimization

Loop optimization Low level optimization Moving code around in a single loop Examples loop invariant code motion, strength reduction, loop unrolling High level optimization Restructuring loops, often affects multiple loops Examples loop fusion, loop interchange, loop tiling

Learn how to improve the performance of loops in compiled programs using various techniques such as induction variable elimination, loop fusion, loop peeling, and loop parallelization. See examples, definitions, and code transformations for each optimization.

Loop Optimization is the process of increasing execution speed and reducing the overheads associated with loops. It plays an important role in improving cache performance and making effective use of parallel processing capabilities.

Learn how compilers optimize loops to improve the efficiency of software. Explore loop unrolling, loop fusion, loop-invariant code motion, and loop blocking with examples and explanations.

Loop Distribution Loop distribution is a somewhat controversial optimization. If the loop is unvectorizable, the optimization can split the loop into vectorizable and unvectorizable parts. Vectorization of one part should bring an increase in speed. However, in practice, there is a problem with this approach. Consider the following example

Learn about the process of increasing execution speed and reducing overheads of loops in compiler theory. Explore various loop transformations, such as fission, fusion, interchange, inversion, and vectorization, and their benefits and challenges.

Loop splitting or peeling carving off the first few iterations of the loop and running them separately, leaving you with a simpler main loop body. Loop transformations for data locality optimization see also Kathryn McKinley's slides on this topic. See overviews of these and still more in Steve Chong's slides on loop optimizations.

Learn how to optimize loops in compiler design by hoisting loop-invariant computation and using induction variables. See examples of code transformation and analysis in SSA form.

Loop optimization is the most valuable machine-independent optimization because the program's inner loop takes the bulk of the time of a programmer. If we decrease the number of instructions in an inner loop then the running time of a program may be improved even if we increase the amount of code outside that loop.

Loop interchange Memory reference optimization Blocking Out-of-core solutions Someday, it may be possible for a compiler to perform all these loop optimizations automatically. Typically loop unrolling is performed as part of the normal compiler optimizations. Other optimizations may have to be triggered using explicit compile-time options.