Conference Information
ScalCom 2026: IEEE International Conference on Scalable Computing and Communications
https://swc-ieee-2026.github.io/scalcom/Submission Date: |
2026-04-01 |
Notification Date: |
2026-07-01 |
Conference Date: |
2026-09-07 |
Location: |
Rende, Italy |
Years: |
26 |
Viewed: 33523 Tracked: 9 Attend: 1
Call For Papers
Scalability is one of the key evaluation criteria of computing systems. High scalability represents a kind of elasticity, which can guarantee high throughput, small delay, and high performance. Scalable computing and communications are particularly crucial in fields such as artificial intelligence, big data processing, and scientific computing, where large-scale data processing or complex computational tasks are common. To boost scalability, it's vital to utilize supportive tools & platforms, and high-performance communications & networking technologies. Additionally, optimizing algorithms and models are essential for efficiently managing increasing workloads and data volumes. Moreover, with the development of AI large model technology, scalable intelligent computing systems are also very important for creating intelligent environments, services and applications. The 26th IEEE International Conference on Scalable Computing and Communications (ScalCom 2026) will include a highly selective program of technical papers, panel discussions and keynote speeches. We welcome high-quality papers that describe original and unpublished research advancing the state of the art in scalable communication & networks. Topics of Interest The topics include (but are not limited to): Parallel and Distributed Programming Models and Tools Cloud and Edge Infrastructure Management Large-Scale Heterogeneous Computing Systems Scalable Cloud, Edge, and Serverless Architectures Distributed Data Management Systems High-Performance and Scalable Networking Scalability Solutions for IoT and Cyber-Physical Systems Energy-Efficient Scalable Computing and Communication Scalable Machine Learning and AI Algorithms Efficient Large-Scale AI Training and Inference Resource Management for AI and Data-Intensive Workloads Security and Privacy in Scalable Computing and AI Systems
Last updated by Dou Sun in 2026-01-18
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