Accelerating K-Means on the Graphics Processor via CUDA

2009 ◽  
Author(s):  
Mario Zechner ◽  
Michael Granitzer
Keyword(s):  
Graphics Processor

Simulations of pulse propagation in optical fibers using graphics processor units

2011 ◽  
Vol 182 (7) ◽  
pp. 1414-1420 ◽  
Author(s):  
J.M. Alcaraz-Pelegrina ◽  
P. Rodríguez-García
Keyword(s):  
Optical Fibers ◽  
Pulse Propagation ◽  
Graphics Processor

GPU Accelerated SVM with Sparse Sliced EllR-T Matrix Format

2015 ◽  
Vol 24 (01) ◽  
pp. 1450012 ◽  
Author(s):  
Krzysztof Sopyla ◽  
Paweł Drozda
Keyword(s):  
Parallel Processing ◽  
Sparse Matrix ◽  
Classification Problems ◽  
Graphics Processor ◽  
Highly Efficient ◽  
Significant Acceleration ◽  
Svm Algorithm ◽  
Memory Footprint ◽  
T Matrix

This paper presents the SECu-SVM algorithm for solving classification problems. It allows for a significant acceleration of the standard SVM implementations by transferring the most time-consuming computations from the standard CPU to the Graphics Processor Units (GPU). In addition, highly efficient Sliced EllR-T sparse matrix format was used for storing the dataset in GPU memory, which requires a very low memory footprint and is also well adapted to parallel processing. Performed experiments demonstrate an acceleration of 4–100 times over LibSVM. Moreover, in the majority of cases the SECu-SVM is less time-consuming than the best sparse GPU implementations and allows for handling significantly larger classification datasets.

scholarly journals Elastic Alignment of Microscopic Images Using Parallel Processing on CUDA-Supported Graphics Processor Units

2010 ◽  
Vol 16 (S2) ◽  
pp. 730-731
Author(s):  
J Michálek ◽  
M Čapek ◽  
J Janáček ◽  
L Kubínová
Keyword(s):  
Parallel Processing ◽  
Graphics Processor ◽  
Microscopic Images

Extended abstract of a paper presented at Microscopy and Microanalysis 2010 in Portland, Oregon, USA, August 1 – August 5, 2010.

Sign in / Sign up

Export Citation Format

Share Document