An Out-of-core GPU Approach for Accelerating Geostatistical Interpolation-Reference-Cited by-同舟云学术

An Out-of-core GPU Approach for Accelerating Geostatistical Interpolation

Published:2014 Issue: Volume:29 Page:888-896
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Allombert Victor,Michea David,Dupros Fabrice,Bellier Christian,Bourgine Bernard,Aochi Hideo,Jubertie Sylvain

Publisher

Elsevier BV

Subject

General Engineering

Reference11 articles.

1. Tangpei Cheng. Accelerating universal kriging interpolation algorithm using CUDA-enabled GPU. Computers and Geosciences, 54:178-183, 2013.

2. Jean Paul Chils and Pierre Delfiner. Geostatistics: Modeling Spatial Uncertainty. Wiley, 2 edition, 2012.

3. Jaeyoung Choi, Jack J. Dongarra, L. Susan Ostrouchovn, Antoine Petitet, David Walker, and Clint Whaley. Design and implementation of the scalapack LU, QR an Cholesky factorization routines. Scientific Programming, 1994.

4. E. Gutirrez de Rav, F.J. Jimnez-Hornero, A.B. Ariza-Villaverde, and J.M. Gmez-Lpez. Using general-purpose computing on graphics processing units (GPGPU) to accelerate the ordinary kriging algorithm. Computers and Geosciences, 2014.

5. Matheron Georges. Principles of geostatistics, volume 58. Economic geology, 1963.

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A compression-based memory-efficient optimization for out-of-core GPU stencil computation;The Journal of Supercomputing;2023-02-20

2. High Performance Multivariate Geospatial Statistics on Manycore Systems;IEEE Transactions on Parallel and Distributed Systems;2021-11-01

3. Beyond 16GB;Proceedings of the Workshop on Memory Centric Programming for HPC;2017-11-12

4. Efficient GPU-Based Parallel Kriging Algorithm for Predicting the Air Quality Index;2017 International Conference on Green Informatics (ICGI);2017-08

5. Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search;SpringerPlus;2016-08-22