HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

An out-of-core GPU approach for accelerating geostatistical interpolation

Abstract : Geostatistical methods provide a powerful tool to understand the complexity of data arising from Earth sciences. Since the mid 70's, this numerical approach is widely used to understand the spatial variation of natural phenomena in various domains like Oil and Gas, Mining or Environmental Industries. Considering the huge amount of data available, standard implementations of these numerical methods are not efficient enough to tackle current challenges in geosciences. Moreover, most of the software packages available for geostatisticians are designed for a usage on a desktop computer due to the trial and error procedure used during the interpolation. The Geological Data Management (GDM) software package developed by the French geological survey (BRGM) is widely used to build reliable three-dimensional geological models that require a large amount of memory and computing resources. Considering the most time-consuming phase of kriging methodology, we introduce an efficient out-of-core algorithm that fully benefits from graphics cards acceleration on desktop computer. This way we are able to accelerate kriging on GPU with data 4 times bigger than a classical in-core GPU algorithm, with a limited loss of performances.
Complete list of metadata

Contributor : Victor Allombert Connect in order to contact the contributor
Submitted on : Wednesday, February 3, 2016 - 9:23:41 AM
Last modification on : Thursday, February 3, 2022 - 2:56:05 PM
Long-term archiving on: : Thursday, November 10, 2016 - 7:37:13 PM


Publisher files allowed on an open archive



Victor Allombert, David Michéa, Fabrice Dupros, Christian Bellier, Bernard Bourgine, et al.. An out-of-core GPU approach for accelerating geostatistical interpolation. Procedia Computer Science, Elsevier, 2014, ⟨10.1016/j.procs.2014.05.080⟩. ⟨hal-01133110⟩



Record views


Files downloads