28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, Västeras, Sweden,

CALL FOR PAPERS Parallel, Distributed, and Network-Based Processing has undergone impressive change over recent years. New architectures and applications have rapidly become the central focus of the discipline. These changes are often a result of cross-fertilisation of parallel and distributed technologies with other rapidly evolving technologies. It is of paramount importance to review and assess these new developments in comparison with recent research achievements in the well-established areas of parallel and distributed computing, from industry and the scientific community. PDP 2020 will provide a forum for the presentation of these and other issues through original research presentations and will facilitate the exchange of knowledge and new ideas at the highest technical level. Topics of interest include, but are not restricted to: Parallel Computing: massively parallel machines; embedded parallel and distributed systems; multi- and many-core systems; GPU and FPGA based parallel systems; parallel I/O; memory organisation. Distributed and Network-based Computing: Cluster, Grid, Web and Cloud computing; mobile computing; interconnection networks. Big Data: large scale data processing; distributed databases and archives; large scale data management; metadata; data intensive applications. Models and Tools: programming languages and environments; runtime support systems; performance prediction and analysis; simulation of parallel and distributed systems. Systems and Architectures: novel system architectures; high data throughput architectures; service-oriented architectures; heterogeneous systems; shared-memory and message-passing systems; middleware and distributed operating systems; dependability and survivability; resource management. Advanced Algorithms and Applications: distributed algorithms; multi-disciplinary applications; computations over irregular domains; numerical applications with multi-level parallelism; real-time distributed applications.