The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
An MPI–CUDA library for image processing on HPC architectures
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“Bu yeni algoritma var olan Brute Force algoritmasından daha iyi sonuç vermiştir.”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [94]
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Cites
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Cited by
GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi
AYDIN, S., SAMET, R., & BAY, Ö. F. (2020) · Politeknik Dergisi · doi:10.2339/politeknik.563767 · Cited by 3
“Ayrıca Zhang ve diğerlerinin [95] 2014 ve Galizia ve diğerlerinin [96] ise 2015 yılında yaptıkları çalışmada kütüphaneler kullanılmaktadır.”
Metadata
- Authors
- Galizia, A., D’Agostino, D., & Clematis, A.
- Affiliations
- Istituto di Matematica Applicata e Tecnologie Informatiche (IT)
- Corresponding author
- Galizia, Antonella
- Venue
- Journal of Computational and Applied Mathematics
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 273
- Pages
- 414-427
- ISSN
- 0377-0427 (ISSN-L)
- OpenAlex
- W2014202388
- Cited by
- 19
- References
- 35
- Citations by year
- 2026: 1 · 2024: 1 · 2022: 1 · 2021: 2 · 2019: 6 · 2017: 1 · 2016: 4 · 2015: 3
- FWCI
- 4.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1461 d)
- Locations
- Journal of Computational and Applied Mathematics (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
- Keywords
- image processing, GPU clusters, MPI, CUDA, heterogeneous computing, GPU acceleration, speedup
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
