Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing
نویسندگان
چکیده
منابع مشابه
Pool evolution: a domain specific parallel pattern
We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling th...
متن کاملPrioritization in Parallel Symbolic Computing
It is argued that scheduling is an important determinant of performance for many parallel symbolic computations, over and above the issues of dynamic load balancing and grainsize control. We propose associating unbounded levels of priorities with tasks and messages as the mechanism of choice for specifying scheduling strategies. We demonstrate how priorities can be used in par-allelizing comput...
متن کاملRPL2: A Language and Parallel Framework for Evolutionary Computing
The Reproductive Plan Language RPL2 is an extensible, interpreted language for writing and using evolutionary computing programs. It supports arbitrary genetic representations, all structured population models described in the literature together with further hybrids, and runs on parallel or serial hardware while hiding parallelism from the user. This paper surveys structured population models,...
متن کاملParallel Patterns for Agent-based Evolutionary Computing
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core architectures available on modern supercomputers. In this paper, we describe an easy and efficient way to implement certain population-based algorithms (in the discussed case, multi-agent computing system) on such runtime environments. Our solution is based on an Erlang software library which im...
متن کاملEfficient Data Mining with Evolutionary Algorithms for Cloud Computing Application
With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Parallel Programming
سال: 2015
ISSN: 0885-7458,1573-7640
DOI: 10.1007/s10766-015-0358-5