Predicting the best mapping for efficient exploitation of task and data parallelism

Fernando Guirado; Ana Ripoll; Concepció Roig; Xiao Yuan; Emilio Luque

Journal ArticleOPEN ACCESS

Predicting the best mapping for efficient exploitation of task and data parallelism

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 2790 218-223

DOI: 10.1007/978-3-540-45209-6_33

2Citations

7Readers

Abstract

The detection and exploitation of different kinds of parallelism, task parallelism and data parallelism often leads to efficient parallel programs. This paper presents a simulation environment to predict the best mapping for the execution of message-passing applications on distributed systems. Using this environment, we evaluate the performance of an image processing application for the different parallelizing alternatives, and we propose the ways to improve its performance. © Springer-Verlag 2003.

Cite

CITATION STYLE

APA

Guirado, F., Ripoll, A., Roig, C., Yuan, X., & Luque, E. (2004). Predicting the best mapping for efficient exploitation of task and data parallelism. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2790, 218–223. https://doi.org/10.1007/978-3-540-45209-6_33

Predicting the best mapping for efficient exploitation of task and data parallelism

Abstract

Cite

Register to see more suggestions