EvoPAR 2016 - Parallel Architectures and Distributed Infrastructures

There is growing interest in running evolutionary computation on Parallel and Distributed Computing Infrastructures. A number of technologies are already available. These include Grid and Cloud Computing, Internet Computing (e.g. seti-AT-home, boinc), General Purpose Computation on Graphics Processing Units (GPGPU), multi-core and many-core architectures and supercomputers. Although they are routinely used for running computing intensive applications, considerable skill is required to get the best from them. The experimenter has to consider scheduling, porting of applications, communication topologies, new parallel models and architectures, cache and memory management optimization, preemptive multitasking and simultaneous multi threading and even energy consumption. Also, the experimenter may need to change their evolutionary algorithm to fully exploit these new tools. At EvoPar scientists and engineers will gather to share and exchange their experiences, discuss challenges, and report state-of-the-art and in-progress research on all aspects of the application of evolutionary algorithms for improving parallel architectures and distributed computing Infrastructures. EvoPAR will assist the two-way flow of ideas between the parallel computing community and the EC community.
Areas of Interest and Contributions
High quality paper submissions which demonstrate novelty in terms of methodology, application or both, were strongly encouraged. Applications of interest included (but were not limited to)
Parallel implementation of evolutionary algorithms.
Optimisation of Parallel architectures by means of EAs.
Hardware implementation of EAs, including but not limited to Field Programmable Gate Arrays. GP-GPU optimization.
Improving Scheduling techniques for P2P and Grid Systems. Improving Scheduling techniques for running distributed EAs.
Improving Fault tolerance techniques for distributed systems and Distributed EAs capabilities for coping with failures.
Analytical modelling and performance evaluation of Parallel and Distributed Infrastructures when running EAs.
Case studies showing the role of Parallel and Distributed Infrastructures in conjunction with Distributed EAs when solving hard real-life problems.