Maximize Parallelism for Nested Loops via Loop Striping

applications are recursive or iterative. Transformation techniques are generally applied to increase parallelism for these nested loops. Most of the existing loop transformations techniques either can not achieve maximum parallelism, or can achieve maximum parallelism but with complicated loop bounds and loop indexes calculations. This paper proposes a new technique, loop striping, that can maximize parallelism while maintaining the original row-wise execution sequence with minimum overhead. Loop striping groups iterations into stripes, where a stripe is a group of iterations in which all iterations are independent and can be executed in parallel. Theorems and efficient algorithms are proposed for loop striping transformations. The experimental results show that loop striping always achieves better iteration period than software pipelining and loop unfolding, improving average iteration period by 50% and 54 % respectively. Key words: Loop Scheduling, Optimization, Loop Transformation