language: en

TR - UCSD - CS96-484

Mapping Parallel Applications to Distributed Heterogeneous Systems

Silvia M. Figueira 1 and Francine Berman 2
Department of Computer Science and Engineering University of California, San Diego
{silvia,berman}@cs.ucsd.edu

Abstract Fast networks have made it possible to coordinate distributed heterogeneous CPU, memory and storage resources to provide a powerful platform for executing high-performance applications. However, the performance of parallel applications on such systems is highly dependent on the mapping of application tasks to machines. In this paper, we propose a mapping strategy for applications formed by multiple tasks targeted to heterogeneous platforms. We first define a mapping model, the match-tree, which reects the data movement and conversion costs of distributed algorithms and allows for alternative implementations of individual tasks on different machines. We then define the find-mapping and split-partition algorithms, based on the match-tree model, to determine the best allocation of tasks to resources in heterogeneous systems. We illustrate the use of these algorithms with a sample distributed application.

1 Introduction