Data and task parallel scheduling for dense linear algebra kernels on heterogeneous clusters

• Type: Article in International Conference Proceedings Book
• Date: 2004

Authors

Celeste Isabel Navarro Morais (Author) Other; Jorge Manuel Gomes Barbosa (Author) FEUP; Miguel Pimenta Monteiro (Author) FEUP

Conference proceedings National

Title: SEIO

Pages: 1-8

XXVIII CONGRESO NACIONAL DE ESTADÍSTICA E INVESTIGACIÓN OPERATIVA

Cádiz, Outubro

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering

Other information

Abstract (EN): The aim of data and task parallel scheduling for dense linear algebra kernels is to minimize the processing time of an application composed by several linear algebra kernels
The scheduling strategy presented here combines the task parallelism used when scheduling independent tasks and the data parallelism used for linear algebra kernels. This problem has been studied for scheduling independent tasks on homogeneous machines. Here it is proposed a methodology for heterogeneous clusters and it is shown that significant improvements can be achieved with this strategy.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8