Abstract
Abstract Solution of today large complex problems may need the combination of several different methods, algorithms and techniques in a distributed computing system with heterogeneous processors, usually interconnected through a communication network. In this context, Team Algorithm is presented as a general technique used to combine different methods and algorithms in a distributed computing system composed of different workstations, personal computers and/or parallel computers. Moreover, experimental results have proved that in many real world problems, Team Algorithms can benefit from the use of asynchronous implementations, speeding up the whole process with an important synergy effect, in a new appealing technique known as Parallel Asynchronous Team Algorithms.
The main idea behind Parallel Asynchronous Team Algorithms is very simple: to partition a large complex problem in small sub-problems that can be solved in different processors of a distributed system with well known sequential methods, combining the partial results of each sub-problem in such a way that a good global solution is finally found. Because each processor works at its own speed and eventually, with its own algorithms, an asynchronous implementation eliminates idle synchronization times speeding up the whole process. Team Algorithms have been successfully applied in the resolution of many engineering problems in which a synergetic effect may take place between different processors.
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Barán, B. (2002). Parallel Asynchronous Team Algorithms. In: Corrêa, R., Dutra, I., Fiallos, M., Gomes, F. (eds) Models for Parallel and Distributed Computation. Applied Optimization, vol 67. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3609-0_9
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