Recent Advances in Parallel Computing and Big Data
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 November 2024 | Viewed by 233
Special Issue Editors
Interests: big data; artificial intelligence; high-performance computing
Special Issues, Collections and Topics in MDPI journals
Interests: data science; time series modeling; artificial intelligence platforms
Special Issue Information
Dear Colleagues,
We are pleased to announce a forthcoming Special Issue titled "Recent Advances in Parallel Computing and Big Data". In the era of advanced computing, the synergy between parallel computing and big data has become pivotal for facilitating research and applications across diverse scientific and industrial domains. This Special Issue aims to highlight significant developments in parallel computing technologies that effectively tackle the challenges in big data analysis, artificial intelligence models and large-scale parallel applications. By focusing on scalable and efficient solutions, we explore how these technologies are critical in various domains.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Innovative parallel algorithms for big data processing;
- Numerical methods and parallel algorithms for the advanced modeling and simulation;
- Use of hardware accelerators (GPUs, FPGA) and heterogeneous hardware in computational science;
- Scalability and performance studies on large-scale systems;
- Architectures and frameworks for integrating big data and parallel computing;
- Machine learning and artificial intelligence approaches;
- Advances in distributed databases and file systems for handling big data;
- Challenges and solutions in data-intensive environments for parallel computing systems
We invite researchers to submit their original research articles, comprehensive review papers and short communications that push the frontiers of knowledge in parallel computing and big data. All submissions will undergo a rigorous peer-review process, ensuring that only high-quality research is published.
Prof. Dr. Jue Wang
Guest Editor
Dr. Meng Wan
Prof. Dr. Rongqiang Cao
Guest Editor Assistants
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- big data
- high-performance computing
- data science
- parallel computing
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