Results 251 to 260 of about 55,131 (288)

GPU-accelerated protein sequence alignment

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (CPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several optimizations to reduce the number of memory accesses ...
Laiq, Hasan, Marijn, Kentie, Zaid, Al-Ars   +2 more
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GPU Accelerated Speech Recognition

2021
Speech recognition technology is one of the quickly developing advanced technologies of engineering. It has various applications in different zones and offers potential points of interest. There is a correlation to pre-requirement for speech recognition and machine learning which is that grammar classification and a method for extraction phonemes from ...
Mohamad Rosyidi Ahmad, Ahmad Fakhri Arif Mat Zaid, Muhamad Husaini Abu Bakar, Mohd Fauzi Alias, Pranesh Krishnan   +4 more
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GPU Acceleration Techniques

2013
This paper introduce the basic concept, implementation, and engineering applications of graphics processor unit (GPU) acceleration of parallel FDTD method based on compute unified device architecture (CUDA). Several typical examples are employed to demonstrate the performance of GPU and VALU acceleration techniques.
Veysel Demir, Atef Elsherbeni, null Wenhua Yu   +2 more
openaire   +1 more source

GPU‐accelerated computation of electron transfer

Journal of Computational Chemistry, 2012
AbstractElectron transfer is a fundamental process that can be studied with the help of computer simulation. The underlying quantum mechanical description renders the problem a computationally intensive application. In this study, we probe the graphics processing unit (GPU) for suitability to this type of problem.
HOEFINGER, SIEGFRIED, ACOCELLA, ANGELA, Pop S. C., Narumi T., Yasuoka K., Beu T., ZERBETTO, FRANCESCO   +6 more
openaire   +3 more sources

GPU accelerated face detection

2010 International Conference on Intelligent Control and Information Processing, 2010
Recently many-core graphic processor units (GPUs) are delivering impressive power for general purpose computing applications. Thanks to their high memory bandwidth and computing throughput, GPUs could often significantly accelerate many applications.
Jiangang Kong, Yangdong Deng
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GPU accelerated dislocation dynamics

Journal of Computational Physics, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ferroni, Francesco, Tarleton, Edmund, Fitzgerald, Steven   +2 more
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GPU-accelerated charge mapping

2016 IEEE High Performance Extreme Computing Conference (HPEC), 2016
Charge Mapping is critical to electrostatics computations such as performed in Molecular Dynamics simulations. It reduces the complexity of evaluating long-range Coulombic forces by diffusing discrete particle charges onto a regular grid. Acceleration of this stage using GPUs is non-trivial, with the compute and memory intensive nature of the algorithm
Ahmed Sanaullah, Saiful A. Mojumder, Kathleen M. Lewis, Martin C. Herbordt   +3 more
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GPU accelerated NEH algorithm

2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS), 2014
This research aims to develop a CUDA accelerated NEH algorithm for the permutative flowshop scheduling problem with makespan criterion. NEH has been shown in the literature as the best constructive heuristic for this particular problem. The CUDA based NEH aims to speed up the processing time by utilising the GPU cores for parallel evaluation.
Magdalena Metlicka, Donald Davendra, Frank Hermann, Markus Meier, Matthias Amann   +4 more
openaire   +1 more source

GPU Accelerated Genetic Clustering

2012
Genetic and evolutionary algorithms have been used to find clusters in data with success. Unfortunately, evolutionary clustering suffers from the high computational costs when it comes to fitness function evaluation. The GPU computing is a recent programming and development paradigm introducing high performance parallel computing to general audience ...
Pavel Krömer, Jan Platoš, Václav Snášel   +2 more
openaire   +1 more source

GPU-Accelerated SAX/GA

2018
This chapter presents several solutions to accelerate the SAX/GA algorithm using a GPU with each solution aiming at maximizing the parallel potential of SAX/GA. The first implementation, Solution A, focuses in the bottleneck identified previously, the SAX transformation, while Solution B and C try to explore a new method to optimize the populations of ...
João Baúto, Rui Neves, Nuno Horta
openaire   +1 more source