The IFIP International Conference on Network and Parallel Computing (NPC) is a prestigious annual gathering that serves as a global platform for researchers, academics, and industry professionals to explore and exchange cutting-edge ideas, research findings, and innovative solutions in the fields of network, distributed and parallel computing.

Topics of interest include, but are not limited to:

Networked, distributed and parallel computing applications and algorithms

• Networked, distributed and parallel computing issues and opportunities with Artificial intelligence applications.
• Networked, distributed and parallel algorithms for computational and data-enabled scientific, engineering, biological, and medical applications.
• Networked, distributed and parallel algorithms for accelerators, neuromorphic architectures, and other emerging architectures.

Networked, distributed and parallel computing architectures and systems

• Computing and network convergence technologies and systems, computing power networks, computing utility
• Emerging architectures and systems at all scales, from embedded, device, edge to cloud.
• Novel distributed and parallel architectures and systems for AI model training and inference, domain-specific accelerators for AI
• High-performance computing, systems for enabling parallelism at extreme scale
• Power-efficient and green computing systems
• Non-traditional Computing Technology
• Neuromorphic architectures and cognitive computing accelerators
• Heterogeneous multicore architectures and accelerators
• In-Memory and near-data computing.
• Network and interconnect architectures.
• Storage systems with novel architectures.

Networked, distributed and parallel computing software environments and tools

• Programming models and compilation for existing and emerging platforms.
• Dataflow programming models, frameworks, languages and environments for data-enabled platforms.
• Virtualization of machines, networks, and storage.
• I/O, file systems, and data management.
• Resource management, scheduling, and load balancing.