Energy-aware mappings of series-parallel workflows onto chip multiprocessors

Anne Benoit (1, 2) , Rami Melhem (3) , Paul Renaud-Goud (1, 2) , Yves Robert (1, 2)

1 GRAAL - Algorithms and Scheduling for Distributed Heterogeneous Platforms
2 LIP - Laboratoire de l'Informatique du Parallélisme
3 Department of Computer Science - University of Pittsburgh

This paper studies the problem of mapping streaming appli- cations that can be modeled by a series-parallel graph, onto a 2-dimensional tiled CMP architecture. The objective of the mapping is to minimize the energy consumption, using dynamic and voltage scaling techniques, while maintaining a given level of performance, reflected by the rate of process- ing the data streams. This mapping problem turns out to be NP-hard, but we identify simpler instances, whose optimal solution can be computed by a dynamic programming algo- rithm in polynomial time. Several heuristics are proposed to tackle the general problem, building upon the theoretical results. Finally, we assess the performance of the heuris- tics through comprehensive simulations using the StreamIt workflow suite and various CMP grid sizes.

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Anne Benoit, Rami Melhem, Paul Renaud-Goud, Yves Robert. Energy-aware mappings of series-parallel workflows onto chip multiprocessors. [Research Report] RR-7521, INRIA. 2011, pp.40. ⟨inria-00560707v2⟩