Publication: Integrating software and hardware hierarchies in an autotuning method for parallel routines in heterogeneous clusters
Authors
Cámara, Jesús ; Cuenca Muñoz, Antonio Javier ; Giménez, Domingo
item.page.secondaryauthor
item.page.director
Publisher
Springer
publication.page.editor
publication.page.department
DOI
https://doi.org/10.1007/S11227-020-03235-9
item.page.type
info:eu-repo/semantics/article
Description
Abstract
A hierarchical approach for autotuning linear algebra routines on heterogeneous platforms is presented. Hierarchy helps to alleviate the difficulties of tuning parallel routines for high-performance computing systems. This paper analyzes the application of the hierarchical approach at both the hardware and software levels, using the basic matrix multiplication and the Strassen multiplication as proof of concept on multicore+coprocessor nodes. In this way, the hierarchical approach allows partial delegation of the efficient exploitation of the computing units in the node to the underlying direct autotuned matrix multiplication used in the base case.
publication.page.subject
Citation
Cámara, J., Cuenca, J. & Giménez, D. Integrating software and hardware hierarchies in an autotuning method for parallel routines in heterogeneous clusters. Journal of Supercomputing, 2020, Vol. 76, pp. 9922–9941
item.page.embargo
1-ene-2999
Collections
Ir a Estadísticas
Sin licencia Creative Commons.