Topic 12: Theory and Algorithms for Parallel Computation


Parallelism permeates all levels of current computing systems, from single CPU machines, to large server farms, to geographically dispersed "volunteers" who collaborate over the Internet. The effective use of parallelism depends crucially on the availability of faithful, yet tractable, computational models for algorithm design and analysis and models of efficient strategies for solving key computational problems on prominent classes of computing platforms. Equally important are good algorithmic models of the way the different system components are interconnected. With the development of new genres of computing platforms, such as multicore parallel machines, desktop grids, clouds, and hybrid GPU/CPU-based systems, new computational models and paradigms are needed that will allow parallel programming to advance into mainstream computing.
High-quality, original papers are solicited which contribute new results on foundational issues regarding parallelism in computing and/or proposing improved approaches to the solution of specific algorithmic problems. Topics of interest include, but are not limited to, the following:


  • Foundations, computational models, and emerging paradigms for parallel, distributed, multiprocessor and network computation
  • Deterministic and randomized parallel algorithms and data structures
  • Lower bounds for key computational problems
  • Models and algorithms for parallelism in memory hierarchies
  • Models and algorithms for real networks (scale-free, small world, wireless networks)
  • Energy-efficient algorithms

Topic Committee

Global chair
Giuseppe F. Italiano, Università di Roma 2 Tor Vergata, Italy

Local chair
Henning Meyerhenke, Karlsruhe Institute of Technology (KIT), Germany

Further members
Guy Blelloch, Carnegie Mellon University, USA
Philippas Tsigas, Chalmers University of Technology, Sweden


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