Preliminary study on the automatic parallelism optimization model for image enhancement algorithms based on Intel's® Xeon Phi-Reference-Cited by-同舟云学术

Preliminary study on the automatic parallelism optimization model for image enhancement algorithms based on Intel's® Xeon Phi

Published:2021-05-06 Issue:16 Volume:33 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Huang Fang¹^ORCID,Yang Hao¹,Tao Jian²^ORCID,Wang Jian³^ORCID,Tan Xicheng⁴^ORCID

Affiliation:

1. School of Recourses and Environment University of Electronic Science and Technology of China (UESTC) Chengdu P.R. China

2. Texas A&M Engineering Experiment Station (TEES) Texas A&M University College Station Texas USA

3. Aerospace Information Research Institute (AIR) Chinese Academy of Sciences (CAS) Beijing P.R. China

4. School of Remote Sensing and Information Engineering Wuhan University Wuhan P.R. China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6260

Reference38 articles.

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2. A Parallel Nonlocal Means Algorithm for Remote Sensing Image Denoising on an Intel Xeon Phi Platform

3. Large-Scale Parallel Method of Moments on CPU/MIC Heterogeneous Clusters

4. Many-Core Branch-and-Bound for GPU Accelerators and MIC Coprocessors

5. WangZN LiuCZ LuY et al.The implementation of multi‐scale retinex image enhancement algorithm based on GPU via CUDA. Paper presented at: Proceedings of the 2010 International Symposium on Intelligent Signal Processing and Communication Systems. Chengdu China; 2010:1‐4; IEEE.