Enhancing the Scope for Automated Code Generation and Parallelism by Optimizing Loops through Loop Unrolling

摘要

Solving a problem can have multiple methods, each having its own merits and demerits. The ultimate level of complexity of solution models is highly subjective in nature because a method easy for one person may be much difficult for others. Moreover, methods friendly for humans need not be suitable for automated systems like computers. Similar is the case among various automated systems too. All depend on the nature of the problem and the solver, availability of resources, optimization requirements and the like. For example, loops in source code reduce the complexity while programming but give additional overhead during execution. So, optimization of programs by reducing the number of loops can make considerable improvement in performance at runtime. There are several techniques for optimizing the loops. This study is based on the popular loop optimization technique known as Loop unrolling which is having own advantages and disadvantages, but able to open up the additional scope for enhanced parallelism and automated code generation.