• International Journal of Contents
• /
• v.1 no.1
• /
• pp.40-44
• /
• 2005

This paper introduces region partitioning method of non-perfect nested loops with non-uniform dependences. This kind of loop normally can't be parallelized by existing parallelizing compilers and transformations. Even when parallelized in rare instances, the performance is very poor. Based on the Convex Hull theory which has adequate information to handle non-uniform dependences, this paper proposes an enhanced region partitioning method which divides the iteration space into minimum parallel regions where all the iterations inside each parallel region can be executed in parallel by using variable renaming after copying.

• International Journal of Contents
• /
• v.3 no.3
• /
• pp.15-19
• /
• 2007

We review some loop partitioning techniques such as loop splitting method by thresholds and Polychronopoulos' loop splitting method for exploiting parallelism from single loop which already developed. We propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the iteration and distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences. The algorithms generalize how to transform general single loops with one dependence as well as with multiple dependences into parallel loops.

• International Journal of Contents
• /
• v.4 no.4
• /
• pp.1-6
• /
• 2008

In this paper, we propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the iteration and distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences (MPSL). By the extension of the MPSL method, we also apply to exploit parallelism from nested loops with simple subscripts, based on cycle shrinking and loop interchanging method. The algorithms generalize how to transform general single loops with non-uniform dependences as well as nested loops with simple subscripts into parallel loops.

• International Journal of Contents
• /
• v.2 no.4
• /
• pp.8-11
• /
• 2006

This paper describes several loop partitioning techniques such as loop splitting method by thresholds and Polychronopoulos' loop splitting method for exploiting parallelism from single loop which already developed. We propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences. The algorithms generalize how to transform general single loops into parallel loops.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.565-569
• /
• 2006

This paper reviews some loop partitioning techniques such as loop splitting method by thresholds and Polychronopoulos' loop splitting method for exploiting parallelism from single loop which already developed. We propose improved loop splitting method for maximizing parallelism of single loops with non-constant dependence distances. By using the distance for the source of the first dependence, and by our defined theorems, we present generalized and optimal algorithms for single loops with non-uniform dependences. The algorithms generalize how to transform general single loops into parallel loops.

• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.204-211
• /
• 2005

This paper introduces three loop splitting methods such as minimum dependence distance method, Polychronopoulous' method, and first dependence method for exploiting parallelism from single loop which already developed. And it also Indicates their several problems. We extend the first dependence method which is the most effective one among three loop splitting methods, and propose more powerful loop splitting method to enhance parallelism on single loop. The proposed algorithm solves several problems, such as anti-flow dependence and g=gcd(a,c) > 1, that the first dependence method has.