Complexity of Multi-dimensional Loop Alignment
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
Optimal loop parallelization for maximizing iteration-level parallelism
CASES '09 Proceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems
KFusion: optimizing data flow without compromising modularity
Proceedings of the 12th annual international conference on Aspect-oriented software development
| Hi-index | 0.00 |
Abstract: Data locality and synchronization overhead are two important factors that affect the performance of applications on multiprocessors. Loop fusion is an effective way of reducing synchronization and improving data locality. Traditional fusion techniques, however either cannot address the case when fusion-preventing dependence exists in nested loops, or cannot achieve good parallelism after fusion. This paper gives a significant improvement by presenting several efficient polynomial-time algorithms to solve these problems. These algorithms combined with the retiming technique allow nested loop fusion in the existence of outmost loop-carried dependence as in the presence of fusion-preventing dependence. Furthermore, the technique is proved to achieve fully parallel execution of the fused loops.