A scalable and energy efficient GPU thread map for m-simplex domains

Abstract

This work proposes a new GPU thread map for m-simplex domains that improves its speedup along with the m-dimension and is energy efficient compared to other state of the art approaches. The main contributions of this work are (i) the formulation of an improved new block-space map H:Zm↦Zm for regular orthogonal simplex domains, which is analyzed in terms of resource usage, and (ii) the experimental evaluation in terms of speedup and energy efficiency with respect to a bounding box approach. Results from the analysis show that H has a potential speedup of up to 2× and 6× for 2 and 3-simplices, respectively. Experimental evaluation shows that H is competitive for 2-simplices, reaching 1.2×∼2.0× of speedup for different tests, which is on par with the fastest state of the art approaches. For 3-simplices H reaches up to 1.3×∼6.0× of speedup making it the fastest. The extension of H to higher dimensional m-simplices is feasible and has a potential speedup that scales as m! given a proper selection of parameters r,β which are the scaling and replication factors of the geometry, respectively. In terms of energy consumption, although H is among the highest in power consumption, it compensates by its short duration, making it one of the most energy efficient approaches. The results of this work show that H is a scalable and energy efficient map that improves the efficiency of GPU applications that need to process m-simplex domains, such as Cellular Automata or PDE simulations, among others.

Publication
Future Generation Computer Systems
Cristobal A Navarro
Cristobal A Navarro
Professor at the Universidad Austral de Chile

Professor at the Universidad Austral de Chile

Nancy Hitschfeld Kahler
Nancy Hitschfeld Kahler
+Lab founder | Full Professor Universidad de Chile

Full Professor at the Department of Computer Science, University of Chile. Her main research interests include geometric modeling, geometric meshes, and parallel algorithms (GPU computing), focused in computational science, and engineering applications.

Rolando Kindelan
Rolando Kindelan
Ph.D student

Student of Computer Science at Universidad de Chile