Parallelization of genetic algorithms using Hadoop Map/Reduce
نویسندگان
چکیده
منابع مشابه
Parallelization of genetic algorithms using Hadoop Map/Reduce
In this paper we present parallel implementation of genetic algorithm using map/reduce programming paradigm. Hadoop implementation of map/reduce library is used for this purpose. We compare our implementation with implementation presented in [1]. These two implementations are compared in solving One Max (Bit counting) problem. The comparison criteria between implementations are fitness converge...
متن کاملUsing Hadoop MapReduce for Parallel Genetic Algorithms: A Comparison of the Global, Grid and Island Models.
The need to improve the scalability of Genetic Algorithms (GAs) has motivated the research on Parallel Genetic Algorithms (PGAs), and different technologies and approaches have been used. Hadoop MapReduce represents one of the most mature technologies to develop parallel algorithms. Based on the fact that parallel algorithms introduce communication overhead, the aim of the present work is to un...
متن کاملA Comparative Analysis of MapReduce Scheduling Algorithms for Hadoop
Today’s Digital era causes escalation of datasets. These datasets are termed as “Big Data” due to its massive amount of volume, variety and velocity and is stored in distributed file system architecture. Hadoop is framework that supports Hadoop Distributed File System (HDFS)for storing and MapReduce for processing of large data sets in a distributed computing environment. Task assignment is pos...
متن کاملMapReduce Functions on GasDay Data Using Hadoop
The GasDay lab at Marquette University forecasts natural gas consumption for 26 Local Distributing Companies around the United States. We have a very large amount of data that has accumulated over the past 19 years, and the lab needs a way to select and process from all of this data to gain insight into our forecasting methods. MapReduce is a pair of functions originally proposed by Jeffrey Dea...
متن کاملHadoop Mapreduce OpenCL Plugin
Modern systems generates huge amounts of information right from areas like finance, telematics, healthcare, IOT devices to name a few, the modern day computing frameworks like Mapreduce needs an ever increasing amount of computing power to sort, arrange and generate insights from the data. This project is an attempt to harness the power of heterogeneous computing, more specifically take benefit...
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: Southeast Europe Journal of Soft Computing
سال: 2012
ISSN: 2233-1859
DOI: 10.21533/scjournal.v1i2.61