Resumo (PT):
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.
Idioma:
Inglês
Tipo (Avaliação Docente):
Científica
Nº de páginas:
8