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Many applications in scientific and engineering domains are structured as large numbers of independent tasks with low granularity. These applications are thus amenable to straightforward parallelization, typically in master-worker fashion, provided that efficient scheduling strategies are available. Such applications have been called divisible-loads because(More)
ÐIn this paper, we address the issue of implementing matrix multiplication on heterogeneous platforms. We target two different classes of heterogeneous computing resources: heterogeneous networks of workstations and collections of heterogeneous clusters. Intuitively, the problem is to load balance the work with different speed resources while minimizing the(More)
This article is devoted to the run-time redistribution of arrays that are distributed in a blockcyclic fashion over a multidimensional processor grid. While previous studies have concentrated on e ciently generating the communication messages to be exchanged by the processors involved in the redistribution, we focus on the scheduling of those messages: how(More)
Mapping applications onto parallel platforms is a challenging problem, that becomes even more difficult when platforms are heterogeneous –nowadays a standard assumption. A high-level approach to parallel programming not only eases the application developer’s task, but it also provides additional information which can help realize an efficient mapping of the(More)
| This paper elaborates on a new view on software pipelining, called decomposed software pipelining, and introduced The approach is to decou-ple the problem into resource constraints and dependence constraints. Resource constraints management amounts to scheduling an acyclic graph subject to processors constraints , a problem for which an eeciency bound is(More)
We consider the problem of allocating a large number of independent, equal-sized tasks to a heterogeneous computing platform. We use a nonoriented graph to model the platform, where resources can have different speeds of computation and communication. Because the number of tasks is large, we focus on the question of determining the optimal steady state(More)
This paper is devoted to scheduling a large collection of independent tasks onto heterogeneous clusters. The tasks depend upon (input) files which initially reside on a master processor. A given file may well be shared by several tasks. The role of the master is to distribute the files to the processors, so that they can execute the tasks. The objective for(More)