Balancing of Web Applications Workload Using Hybrid Computing (CPU–GPU) Architecture-Reference-Cited by-同舟云学术

Balancing of Web Applications Workload Using Hybrid Computing (CPU–GPU) Architecture

Published:2023-12-21 Issue:1 Volume:5 Page:
ISSN:2661-8907
Container-title:SN Computer Science
language:en
Short-container-title:SN COMPUT. SCI.

Author:

Chandrashekhar B. N.,Kantharaju V.,Harish Kumar N.,Kumble Lithin

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s42979-023-02444-2.pdf

Reference23 articles.

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2. Pinel F, Dorronsoro B, Bouvrya P. Solving very large instances of the scheduling of independent tasks problem on the GPU. J Parallel Distrib Comput. 2013;73:101–10.

3. Lang J, Rünger G. Dynamic distribution of workload between CPU and GPU for a parallel conjugate gradient method in an adaptive FEM. 2013. p. 299–308. https://doi.org/10.1016/j.procs.2013.05.193

4. Zellmann S, Wald I, Sahistan A, Hellmann M, Usher W. Design and evaluation of a GPU streaming framework for visualizing time-varying AMR data. In: In Eurographics Symposium on Parallel Graphics and Visualization. 2022. p. 61–71. https://doi.org/10.2312/pgv.20221066.

5. Scogland T, Rountree B, Feng W, de Supinski B. Heterogeneous task scheduling for accelerated OpenMP. In: 2012 IEEE 26th International conference proceedings; 2022. p. 151–62. https://doi.org/10.1145/2628071.2628088

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