Locality-improved FFT implementation on a graphics processor
ISCGAV'07 Proceedings of the 7th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
An adaptive inverse-distance weighting spatial interpolation technique
Computers & Geosciences
MCUDA: An Efficient Implementation of CUDA Kernels for Multi-core CPUs
Languages and Compilers for Parallel Computing
The Extraction of Snow Cover Information Based on MODIS Data and Spatial Modeler Tool
ETTANDGRS '08 Proceedings of the 2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing - Volume 01
Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Scene Recognition Acceleration Using CUDA and OpenMP
ICISE '09 Proceedings of the 2009 First IEEE International Conference on Information Science and Engineering
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
GPGPU for cheaper 3D MMO servers
TELE-INFO'10 Proceedings of the 9th WSEAS international conference on Telecommunications and informatics
hiCUDA: High-Level GPGPU Programming
IEEE Transactions on Parallel and Distributed Systems
Computation of filtered back projection on graphics cards
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
A parallel processing of spatial data interpolation on computing cloud
Proceedings of the Fifth Balkan Conference in Informatics
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The aim of this work is the depth of the snow cover computing in the desired point based on the geographical characteristics of a specific geographical point in a modeled area. The measured data are known on few places. These places are coincident with raingauge stations. These data have been collected by many continuous observations and measurements at the specific climatologic raingauging stations of Slovak Hydrometeorogical Institute. An interpolation method is necessary to obtain a representation of real situation about whole surface. The main characteristic of the interpolation computing is the fact that it is time-consuming. In paper, we present two cheap approaches of HPC. The first solution is a utilization of graphics processing units (GPUs) where the availability of enormous computational performance of easily programmable GPUs can rapidly decrease time of computing. The second one is a utilization of multithread CPUs. In our article we demonstrate how to deploy the CUDA architecture, which utilizes the powerful parallel computation capacity of GPU, to accelerate computational process of snow cover depth using the inversedistance weighting (IDW) method. The performance of GPU we face with OpenMP implementation of IDW method. We consider variable number of threads per CPU. The outputs are visualized by the GIS Grass tool.