Results 11 to 20 of about 175,847 (284)

GPU Computing

open access: yesProceedings of the IEEE, 2008
The graphics processing unit (GPU) has become an integral part oftoday's mainstream computing systems. Over the past six years, therehas been a marked increase in the performance and capabilities ofGPUs. The modern GPU is not only a powerful graphics engine but also ahighly-parallel programmable processor featuring peak arithmetic andmemory bandwidth ...
Owens, John D   +5 more
openaire   +5 more sources

Analysis of GPU Computation of Parabolic, Bessel, Wright and Riemann Zeta Functions [PDF]

open access: yesITM Web of Conferences, 2021
This paper deals with GPU computing of special mathematical functions that are used in Fractional Calculus. The graphics processing unit (GPU) has grown to be an integral part of nowadays’s mainstream computing structures.
Jadhav Ashish A.   +4 more
doaj   +1 more source

A unified schedule policy of distributed machine learning framework for CPU-GPU cluster

open access: yesXibei Gongye Daxue Xuebao, 2021
With the widespread using of GPU hardware facilities, more and more distributed machine learning applications have begun to use CPU-GPU hybrid cluster resources to improve the efficiency of algorithms.

doaj   +1 more source

Max-Tree Computation on GPUs

open access: yesIEEE Transactions on Parallel and Distributed Systems, 2022
In Mathematical Morphology, the max-tree is a region-based representation that encodes the inclusion relationship of the threshold sets of an image. This tree has proved useful in numerous image processing applications. For the last decade, work has led to improving the construction time of this structure; mixing algorithmic optimizations, parallel and
Blin, Nicolas   +4 more
openaire   +2 more sources

Fine-Grained Allocation Algorithm for Sharing Heterogeneous Resources in Data Center

open access: yesXibei Gongye Daxue Xuebao, 2020
Data in a data center are stored dispersively. The data-oriented task computing disperses big data analysis tasks to different computing nodes. The extensive use of graphics processing unit (GPU) makes it urgent and important to study how to reasonably ...

doaj   +1 more source

Adopting GPU computing to support DL-based Earth science applications

open access: yesInternational Journal of Digital Earth, 2023
With the advancement of Artificial Intelligence (AI) technologies and accumulation of big Earth data, Deep Learning (DL) has become an important method to discover patterns and understand Earth science processes in the past several years.
Zifu Wang   +7 more
doaj   +1 more source

GPU computing for systems biology [PDF]

open access: yesBriefings in Bioinformatics, 2010
The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate ...
L. Dematte, Prandi, Davide
openaire   +4 more sources

Accelerating NTRU Encryption with Graphics Processing Units [PDF]

open access: yesInternational Journal of Networked and Distributed Computing (IJNDC), 2014
Lattice based cryptography is attractive for its quantum computing resistance and efficient encryption/ decryption process. However, the Big Data issue has perplexed most lattice based cryptographic systems since the overall processing is slowed down too
Tianyu Bai   +4 more
doaj   +1 more source

Fast reconstruction of X-ray dynamic micro-CT based on GPU parallel computing

open access: yesHe jishu, 2021
BackgroundMassive projection data are produced by user experiments with the X-ray dynamic micro-computed tomography (CT) method on the X-ray imaging beamline at Shanghai synchrotron radiation facility (SSRF).
ZHANG Yuan   +5 more
doaj   +1 more source

Multi-GPU-Parallel and Tile-Based Kernel Density Estimation for Large-Scale Spatial Point Pattern Analysis

open access: yesISPRS International Journal of Geo-Information, 2023
Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it is computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges.
Guiming Zhang, Jin Xu
doaj   +1 more source

Home - About - Disclaimer - Privacy