International Conference on Parallel Processing and Applied Mathematics PPAM'2019

Країна: Польща

Місто: Bialystok

Тези до: 21.04.2019

Дати: 08.09.19 — 11.09.19

Область наук: Фізико-математичні;

Швидкі посилання

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Е-мейл Оргкомітету:

Організатори: Institute of Computer & Information Science Czestochowa University of Technology


The PPAM 2019 conference, thirteenth in a series, will cover topics in parallel and distributed computing, including theory and applications, as well as applied mathematics. The focus will be on models, algorithms, and software tools which facilitate efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications, including artificial intelligence and machine learning problems.

PPAM is a biennial conference started in 1994, with the proceedings published by Springer in the Lecture Notes in Computer Sciences series. In 2019 the PPAM conference will take place in Bialystok, the largest city in northeastern Poland, academic and cultural centre, located close to the world-famous Bialowieza Forest.

The PPAM 2019 conference is organized by the Department of Computer and Information Science of the Czestochowa University of Technology together with the Bialystok University of Technology, under the patronage of the Committee of Informatics of the Polish Academy of Sciences, in technical cooperation with the IEEE Computer Society and IEEE Computational Intelligence Society.

Topics of interest include, but are not limited to:

  • Parallel/distributed architectures, enabling technologies
  • Cluster, cloud and fog computing
  • Multi-core and many-core parallel computing, GPU computing
  • Heterogeneous/hybrid computing and accelerators
  • Parallel/distributed algorithms: numerical and non-numerical
  • Scheduling, mapping, load balancing
  • Performance analysis and prediction
  • Performance issues on various types of parallel systems
  • Auto-tuning and auto-parallelisation: methods, tools, and applications
  • Power and energy aspects of computation
  • Parallel/distributed programming
  • Tools and environments for parallel/distributed computing
  • Security and dependability in parallel/distributed environments
  • HPC numerical linear algebra
  • HPC methods of solving differential equations
  • Evolutionary computing, meta-heuristics and neural networks
  • Machine learning, artificial intelligence and HPC
  • HPC interval analysis
  • Applied Computing in mechanics, material processing, biology and medicine, physics, chemistry, business, environmental modeling, etc.
  • Applications of parallel/distributed computing
  • Methods and tools for parallel solution of large-scale problems, including artificial intelligence and machine learning applications
  • Neuromorphic computing

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