Bio-inspired computing is one of the most important tools for complex systems and problems evaluation. Some of the recent methods are neural networks and Evolutionary Algorithms (EAs). Differential Evolution, Particle Swarm (Swarm Intelligence), Scatter Search, Genetic Algorithms and Self-Organizing Migrating Algorithm, amongst others. Other techniques, such as Genetic Programming or similar techniques, are widely used today in order to get elegant solutions of complex systems in reasonable time. Examples of such systems can be seen in ordinary world around us and of course in almost every science discipline, including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economies (exchange rate and stock markets), population growth, physics (control of plasma) and chemistry for example.
Computational complexity of many problems is so big that standard as well as evolutionary techniques, together with methods of High Performance Computing (HPC), have to be used to get practical results in acceptable time. Today, the HPC ranges from supercomputers to general purpose GPUs and multicore processors. The implementation and use of bio-inspired computing in the area of HPC represents an opportunity for revision of old models and technologies as well as for introduction of new models, techniques, and tools.
This track will establish a forum for the presentation and discussion of recent trends in the area of intersection of bio-inspired computing and HPC for researchers, students and academics.

The Workshop topics include (but are not limited to) the following:
-Evolution in Grid Mathematica
-Parallelized Genetic Programming Techniques
-Complex Networks and Evolution
-Evolution and Cloud Computing
-Evolution and Classical HPC
-Evolution and GPGPUs
-Paralellized neural networks
-Application of Parallelized Evolution
-Cellular automata
-Emergent systems: ants, termites, bees, wasps
-Artificial life
-Artificial immune systems
-Rendering (computer graphics) ↔ patterning and rendering of animal skins, bird feathers, mollusk shells and bacterial colonies
-Lindenmayer systems
-Membrane computers
-Behavior based robotics
-Natural computation
-Organic computing
-Swarm intelligence