Combining Fusion Optimizations and Piecewise Execution of Nested Data-Parallel Programs

Authors:
W. Pfannenstiel
Affiliations:
-
Venue:
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Year:
2000

Citing 5
Cited 0

Compiling collection-oriented languages onto massively parallel computers

Journal of Parallel and Distributed Computing - Massively parallel computation
Fine-grain multithreading with minimal compiler support—a cost effective approach to implementing efficient multithreading languages

Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
On the Distribution Implementation of Aggregate Data Structures by Program Transformation

Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Piecewise Execution of Nested Data-Parallel Programs

LCPC '95 Proceedings of the 8th International Workshop on Languages and Compilers for Parallel Computing
Piecewise Execution of Nested Parallel Programs - A Thread-Based Approach

Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Nested data-parallel programs often have large memory requirements due to their high degree of parallelism. Piecewise execution is an implementation technique used to minimize the space needed. In this paper, we present a combinination of piecewise execution and loop-fusion techniques. Both a formal framework and the execution model based on threads are presented. We give some experimental results, which demonstrate the good performance in memory consumption and execution time.