In evolutionary computation, environment is considered essential to realize “evolution” since it is necessary to have enough resources and complexities in the environment for the individuals to evolve. Cloud systems may even offer tens of thousands of virtual machines, terabytes of memories and exabytes of storages. Current trend toward many-core architecture increases the number of cores even more dramatically: we may have more than a million of cores to offer extremely massive parallelization.
In this special session, we discuss parallel and distributed evolutionary computation in the cloud era such as implementation of massively parallel evolutionary algorithms employing cloud computing systems and services, parallel implementation of evolutionary algorithms on many-core architectures including GPUs, and we also welcome any types of parallel and distributed evolutionary computation on any “informal” types of computing environment in this special session including the following themes.
- Implementation of parallel and distributed evolutionary computation in cloud computing systems and/or services
- Implementation of massively parallel evolutionary computation on many-core architecture such as GPUs
- Parallel and distributed evolutionary machine learning techniques
- Design and theory of scalable evolutionary algorithms
- Development of parallel and distributed evolutionary computation framework in cloud computing systems
- Applications of parallel and evolutionary computation techniques in cloud or other modern computing environment
- Applications of EC and other bioinspired paradigms to peer to peer systems, and distributed EC algorithms that use them.
- Voluntary, sneaky or parasite computing using the browser or other widely available infrastructure. Zero-cost distributed computing.
Masaharu Munetomo, Information Initiative Center, Hokkaido University, Japan. firstname.lastname@example.org
Masaharu Munetomo is a professor and vice-director of Information Initiative Center, Hokkaido University, and a chief architect of “Hokkaido University Academic Cloud”, the largest academic cloud system in Japan to conduct research projects realizing a national inter-cloud infrastructure. He has published more than 100 papers in the field of evolutionary computation including advanced evolutionary algorithms based on linkage identification, and distributed systems including cloud computing. He co-organized a special session “EC on Many-core Architecture to Solve Large-scale Problems” in CEC2011 at New Orleans, “Parallel and Distributed Evolutionary Computation in the Cloud Era” in CEC2012 at Cancun, and a member of program committee of CEC since 2002.
Juan Julián Merelo Guervós, department of Computer Architecture and Technology of the University of Granada, Spain.
Juan Julián Merelo Guervós was born in Úbeda, Jaén, España, in March 10th, 1965. Obtained a degree in Physics (majoring in Theoretical Physics) from the University of Granada in 1988 and his PhD in Physics in 1994 from the same University. He is professor from November 2009, attached to the department of Computer Architecture and Technology of the University of Granada. His research topics are mainly within the area of soft computing, including neural networks, evolutionary algorithms, complex networks and combinations of them. He has been working also on implementations of the above mentioned algorithms using overlay networks and other distributed computing methods, such as peer to peer systems. He has been organizer of several workshops, including one on Informal Distributed Evolutionary Computation at CEC 2011, and coorganizer of several Parallel Problem Solving from Nature, including chairing PPSN 2002 which was held at Granada.