Improving Performance and Energy Efficiency of Geophysics Applications on GPU Architectures

Pablo J Pavan (1) , Matheus S Serpa (1) , Emmanuell D Carreño (2) , Víctor Martínez (1) , Edson Padoin (3, 1) , Philippe Navaux (4) , Jairo Panetta (5) , Jean-François Mehaut (6)

1 UFRGS - Instituto de Informática da UFRGS
2 Department of Informatics [Federal University of Paraná]
3 UNIJUI - Universidade Regional do Noroeste do Estado do Sul [Ijuí]
4 UFRGS - Universidade Federal do Rio Grande do Sul [Porto Alegre]
5 Technological Institute of Aeronautics
6 LIG - Laboratoire d'Informatique de Grenoble

Energy and performance of parallel systems are an increasing concern for new large-scale systems. Research has been developed in response to this challenge aiming the manufacture of more energy efficient systems. In this context, this paper proposes optimization methods to accelerate performance and increase energy efficiency of geophysics applications used in conjunction to algorithm and GPU memory characteristics. The optimizations we developed applied to Graphics Processing Units (GPU) algorithms for stencil applications achieve a performance improvement of up to 44.65% compared with the read-only version. The computational results have shown that the combination of use read-only memory, the Z-axis internalization and reuse of specific architecture registers allow increase the energy efficiency of up to 54.11% when shared memory was used and increase of up to 44.53% when read-only was used.

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

Pablo J Pavan, Matheus S Serpa, Emmanuell D Carreño, Víctor Martínez, Edson Padoin, et al.. Improving Performance and Energy Efficiency of Geophysics Applications on GPU Architectures. Latin America High Performance Computing Conference (CARLA), Sep 2018, Bucaramanga, Colombia. ⟨hal-01911234⟩