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, models of computation for algorithm design and analysis, and on efficient strategies for solving key computational problems on prominent classes of computing platforms. No less important are good models of the way the different components/subsystems of a platform 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 models and paradigms are needed that will allow parallel programming to advance into mainstream computing. Topic 12 focuses on contributions providing new results on foundational issues regarding parallelism in computing, and/or proposing improved approaches to the solution of specific algorithmic problems. This year, papers submitted to Topic 12 covered a considerable amount of subjects indicated in the call for papers, among the others, communication complexity issues on various computational models, parallel algorithms and data structures for combinatorial optimization problems, and finally parallelization of loop and finite automata computations. Submissions indicated a significant interest of the parallel computing community towards developing new sound and solid methods for parallel problem solving as well as towards investigating the limitations of parallelism.
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