New Advances in Parallel and Distributed Computing

Dear Colleagues,

This Special Issue focuses on emerging advances that enhance the performance, scalability, and intelligence of parallel and distributed computing systems. It emphasizes new technologies and paradigms in high-performance computing (HPC) in the era of AI, particularly in the context of the convergence of HPC, cloud, and edge computing. The Special Issue is designed to highlight innovations that enable intelligent orchestration, data-driven optimization, cross-facility smart workflows, and energy-efficient computing at scale.

Topics of interest include, but are not limited to, the following:

• Advanced architectures for the HPC–cloud–edge computing continuum.
• Parallel and distributed algorithms for large-scale AI and large language models (LLMs).
• Data-driven optimization techniques for complex scientific and AI workflows.
• Cross-facility resource management and scheduling.
• Workflow management frameworks for distributed and federated infrastructures.
• Performance modeling, optimization, and benchmarking of distributed systems.
• Disaggregated storage and high-throughput data flow optimization.
• Green and sustainable computing strategies for data-intensive workloads.
• Integration of HPC, quantum, and AI accelerators into distributed platforms.
• Emerging applications, including digital twins, autonomous systems, IoT, and 6G networking.

The purpose of this Special Issue is to provide a forward-looking forum for researchers and practitioners to present innovative advances that bridge theory, systems, and applications in next-generation parallel and distributed computing. It seeks to highlight ongoing technological transitions—from conventional high-performance computing (HPC) toward intelligent, adaptive, and converged computing ecosystems—and to stimulate cross-disciplinary dialog that shapes future developments in computing infrastructure, software frameworks, and algorithmic design.

Although extensive research has been conducted in parallel computing, cloud infrastructures, and AI systems, much of the existing literature treats these areas in isolation. This Special Issue explicitly emphasizes their convergence, particularly examining how progress in cloud technologies and AI acceleration is transforming traditional HPC paradigms. By integrating emerging directions in data-driven optimization, AI-assisted orchestration, and energy-aware system design, the issue complements prior work published in venues such as IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, IEEE Access, and Future Generation Computer Systems, and offers a holistic perspective on recent advances and open challenges across the evolving computing continuum.

Dr. Chen Wang
Dr. Jae-Seung Yeom
Dr. Qinglei Cao
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Electronics 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.

• high-performance computing
• parallel and distributed systems
• parallel I/O
• storage systems
• cloud computing
• big data
• large-scale machine learning
• resource management
• network computing
• energy-efficient systems
• fault tolerance
• scalability