Topic 12: Theory and Algorithms for Parallel Computation


Parallelism permeates all levels of current computing systems, from single CPU machines, to large server farms, supercomputers, clouds, and even Internet-based volunteer computing infrastructures. The effective use of parallelism depends crucially on the availability of faithful, yet tractable, computational models for algorithm design and analysis, and of efficient algorithmic strategies for solving key computational problems on prominent classes of platforms. Equally important are good models for the interconnection and the interaction of different system components. 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 propose novel algorithms for the solution of specific computational problems. Topics of interest include, but are not limited to, the following:


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

Topic Committee

Global Chair
Andrea Pietracaprina, University of Padova, Italy

Local Chair
Pedro Ribeiro, University of Porto, Portugal

Further Members
Kieran Herley, University College Cork, Ireland
Sergei Vassilvitskii, Google, USA