Parallel Computing and Artificial Intelligence
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Network Virtualization and Edge/Fog Computing".
Deadline for manuscript submissions: 20 September 2026 | Viewed by 12
Special Issue Editors
Interests: big data; parallel computing
Special Issue Information
Dear Colleagues,
In this Special Issue, ‘Parallel Computing and Artificial Intelligence’, we aim to showcase recent advances at the intersection of high-performance computing and intelligent systems. Modern AI workloads—ranging from deep learning to large-scale data analytics—demand unprecedented computational power, driving the need for optimized parallel algorithms, heterogeneous architectures, and scalable software frameworks. At the same time, AI techniques are increasingly applied to enhance performance modeling, resource allocation, and system optimization in parallel and distributed environments. We invite original research and reviews that explore novel models, algorithms, tools, and applications leveraging parallelism to accelerate AI, as well as AI-driven approaches that improve efficiency and reliability in parallel computing systems. Contributions addressing emerging hardware, edge–cloud orchestration, green HPC, digital twins, or domain-specific accelerators are particularly welcome. Our goal is to provide a comprehensive overview of the cutting-edge developments shaping the future of intelligent and scalable computation.
Topics of interest include, but are not limited to, the following:
- parallel and distributed algorithms for AI and machine learning
- scalable training and inference methods for deep learning
- high-performance computing architectures for AI workloads
- GPU, TPU, FPGA, and heterogeneous accelerator-based computation
- AI-driven optimization of parallel systems, scheduling, and resource management
- performance modeling, simulation, and benchmarking of AI and HPC applications
- parallel programming models, runtimes, and compilers for intelligent systems
- edge–cloud continuum, fog computing, and distributed AI frameworks
- energy-efficient and green HPC techniques for AI pipelines
- digital twins for performance prediction and system optimization
- big data analytics and large-scale scientific computing supported by AI
- parallel processing for autonomous systems, robotics, and cyber–physical systems
- fault tolerance, reliability, and resilience in AI-intensive parallel environments
- domain-specific accelerators and specialized hardware for AI
- applications of parallel AI in healthcare, industry, environment, and societal modeling
- parallel and distributed simulations for large-scale applications
Dr. Veronica Gil-Costa
Dr. Alonso Inostrosa Psijas
Guest Editors
Manuscript Submission Information
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Keywords
- parallel computing
- artificial intelligence
- high-performance computing (HPC)
- scalable algorithms
- heterogeneous architectures
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