Workshop at CP-AI-OR'13

IBM Research Center, Yorktown Heights, NY, USA
May 19, 2013
Main conference: CP-AI-OR'13

This workshop is the continuation of the CP2011 "Workshop on Parallel Methods for Constraint Solving" 
and the 2012 Shonan Meeting on "Parallel Methods for Constraint Solving and Combinatorial Optimization".

It is held in the spirit of the Dagstuhl Seminars (in Germany) or Shonan Meetings (in Japan), that is, a day of brainstorming and open discussion about some common scientific topics, bringing researchers from various backgrounds and aiming at maximal interaction between participants, rather than a sequence of sharply focused talks with little interaction with the audience.

This meeting is designed to be a forum for researchers willing to tackle issues related to the workshop topics, in order to exchange ideas,  theoretical frameworks, design of algorithms and methods, implementation issues, experimental results and to further boost this growing area of research through cross-fertilization.

Workshop Topics

In the last decade, with the development of multi-core workstations, the availability of GPGPU-enhanced systems and the access to Grid platforms and supercomputers worldwide, Parallel Programming reached mainstream programming and appeared as a key issue in order to use in an efficient manner 
the computing power at hand. With the move towards Exascale computing during this decade, this trend will develop all the more.

Search methods and combinatorial optimization techniques are not isolated from this phenomenon, as bigger computing power means the ability to attack more complex combinatorial problems. In the last years some experiments have been done to extend to parallel execution search methods such as Constraint Programming or SAT solving (Boolean satisfiability), and combinatorial optimization methods such as Local Search, Meta-heuristics and Brand & Bound.

However these works have mostly been done for shared memory multi-core systems (i.e. with a few cores) or for small PC clusters (a few machines). The next challenge is to devise efficient techniques and algorithms for massively parallel computers with tens or hundreds of thousands of cores in the form of heterogeneous hybrid systems based on both multi-core processors and GPUs.


We would like to provide a cross-community forum for researchers working on search methods (Constraint Solving, SAT solving, Artificial Intelligence, Logic Programming, etc), combinatorial optimization methods (metaheuristics, local search, tabu search, evolutionary algorithms, ant colony optimization, particle swarm optimization, memetic algorithms, and other types of algorithms) and High Performance Computing (Grids, large PC clusters, massively parallel computers, GPGPUs) in order to tackle the challenge of efficient implementations of search and optimization methods on all kinds of parallel hardware: multi-core, GPU-based or heterogeneous massively parallel systems.