Scheduling strategies for mixed data and task parallelism on heterogeneous processor grids

Abstract : In this paper, we consider the execution of a complex application on a heterogeneous "grid" computing platform. The complex application consists of a suite of identical, independent problems to be solved. In turn, each problem consists of a set of tasks. There are dependences (precedence constraints) between these tasks. A typical example is the repeated execution of the same algorithm on several distinct data samples. We use a non-oriented graph to model the grid platform, where resources have different speeds of computation and communication. We show how to determine the optimal steady-state scheduling strategy for each processor (the fraction of time spent computing and the fraction of time spent communicating with each neighbor). This result holds for a quite general framework, allowing for cycles and multiple paths in the platform graph.
Document type :
Reports
Complete list of metadatas

https://hal-lara.archives-ouvertes.fr/hal-02101992
Contributor : Colette Orange <>
Submitted on : Wednesday, April 17, 2019 - 9:11:31 AM
Last modification on : Wednesday, May 8, 2019 - 1:34:27 AM

File

RR2002-20.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02101992, version 1

Collections

Citation

Olivier Beaumont, Arnaud Legrand, Yves Robert. Scheduling strategies for mixed data and task parallelism on heterogeneous processor grids. [Research Report] LIP RR-2002-20, Laboratoire de l'informatique du parallélisme. 2002, 2+13p. ⟨hal-02101992⟩

Share

Metrics

Record views

2

Files downloads

16