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Themes and Symposia


If a ParCo2022 conference is offered, this will cover the state of the art in the development, applications, and future trends in parallel computing for both High Performance (HPC) and Data Intensive Computing (DIC). The scope will encompass all platforms, from Internet of Things (IoT) and Robotics to HPC systems, Clouds, Quantum, and Neuro-Computing.

The conference will address all aspects of parallel computing, including applications, hardware and software technologies, and languages and development environments.


Section 1: Architectures

New concepts for parallel computing architectures for all levels of parallelism, including:

  • Multicore and manycore systems
  • Heterogeneous systems
  • Accelerators, including GPUs and FPGAs
  • High-performance systems, including peta- and exascale
  • Architectures for handling large data sets and data intensive computing, including high speed storage systems
  • Interconnection networks
  • Clouds for HPC
  • Performance evaluation
  • Energy saving designs
  • IoT and mobile devices
  • Brain-inspired systems, including neurocomputing
  • Quantum computers
  • Specialised architectures for high-performance machine learning and deep learning.

Section 2: Software

Software for parallel computing platforms, including

  • Operating systems and middleware for all types of parallel architectures
  • Software engineering methodologies, and methods and tools for developing and maintaining parallel software
  • Parallel programming languages, compilers, libraries, and environments
  • Testing and debugging techniques and tools
  • Best practices of parallel computing on multicore, manycore, and stream processors
  • Design patterns for parallel computing.

Section 3: Algorithms

Design, analysis, and implementation of parallel algorithms for all application areas, emphasising the parallel computing aspects and focusing on issues such as:

  • Scalability and speedup
  • Efficient utilization of the memory hierarchy
  • Communication and synchronization
  • Data management
  • Energy awareness.

Section 4: Applications

The application of parallel computing to solve all types of business, industrial, scientific, and engineering problems using high-performance computing technologies, in particular:

  • Astronomy and space
  • Health science and care
  • Geo- and environmental sciences
  • Computational chemistry
  • Material science
  • Bioinformatics
  • Exploration and optimal use of resources
  • Manufacturing
  • Data intensive (big data) analytics and applications
  • Economic and financial modelling
  • Learning systems (deep learning) and AI
  • Robotics
  • Automonous transport systems, including self driving vehicles
  • Virtual and augmented reality (VR and AR).


Proposals for organising a symposium are welcomed.

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Last updated: 2021-10-19