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PaSeO 2017 -- Parallel Search and Optimisation
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Joint Workshop of CP 2017, ICLP 2017 and SAT 2017
Melbourne, Australia, August 28th, 2017
(immediately following IJCAI 2017 )

https://sites.google.com/view/paseo17


Important Dates
Paper submission: June 14, 2017
Notification: July 7, 2017

PaSeO is the fifth workshop of a series started with the CP 2011
"Workshop on Parallel Methods for Constraint Solving" (Perugia,
Italy), the 2012 Shonan Meeting on "Parallel Methods for Constraint
Solving and Combinatorial Optimization" (Shonan Village, Japan), the
CPAIOR 2013 workshop on "Parallel Methods for Combinatorial Search &
Optimization" (New York, USA), and the ParSearchOpt14 workshop et the
Vienna Summer of Logic (Austria).

It will be 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 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.

Aims and Scope
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Over the last decade, with the development of multi-core workstations,
the availability of hybrid GPGPU-enhanced systems and the increasingly
generalized access to Grid and Cloud platforms as well as
supercomputers worldwide, Parallel Programming has met with the
mainstream. It appears as a key concern in order to use in an
efficient manner the computing power at hand.

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 many experiments have been done to parallelize the execution of
search methods such as SAT solving, Constraint Programming and
combinatorial optimization methods such as Local Search,
Meta-heuristics and Branch & Bound. However most these works have
mostly been done for shared memory multi-core systems (i.e. with a few
cores or tens of cores) or for small PC clusters (a few machines or
tens of 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 GPU. With the move to
Exascale computing probably by the end of this decade, this trend will
continue to gain importance.

An important aspect for researchers working on parallel search and
optimization in different fields is to share their experience on both
theoretical and practical issues. This workshop is thus aimed to be a
forum for researchers willing 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 and Paper Submission
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We would like to provide a cross-community forum for researchers
working on search methods (Constraint Solving, Logic Programming, SAT
solving, Artificial Intelligence, 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.

We thus solicit papers on the above topics, including reports on work
in progress, as well as position papers.

Papers must be between 5 to 15 pages plus references and use the
Springer LNCS style and should be submitted through EasyChair at:

https://easychair.org/conferences/?conf=paseo2017.

Organizers
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Philippe Codognet, University Pierre & Marie Curie, Paris, France (Chair)
Salvador Abreu, University of Evora, Portugal
Daniel Diaz, University of Paris-1, France

Program Committee
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Salvador Abreu (University of Evora, Portugal)
Alejandro Arbelaez (Cork Institute of Technology, Ireland)
Philippe Codognet (University Pierre & Marie Curie, Paris, France)
Daniel Diaz (University of Paris-1, France)
Youssef Hamadi (Ecole Plytechnique, France)
Arnaud Lalouet (Huawei Technologies, France)
Ines Lynce (University of Lisbon, INESC-ID/IST, Portugal)
Enrico Pontelli (New Mexico State University, USA)
Lakhdar Sais (Université d'Artois / CRIL, France)
Vijay Saraswat (IBM Research, USA)
Christian Schulte (KTH Royal Institute of Technology, Sweden)