Thursday 28th of March 2024
 

Towards a next generation of scientific computing in the Cloud


Yassine Tabaa and Abdellatif Medouri

More than ever, designing new types of highly scalable data intensive computing is needed to qualify the new generation of scientific computing and analytics effectively perform complex tasks on massive amounts of data such as clustering, matrix computation, data mining, information extraction … etc. MapReduce, put forward by Google, is a well-known model for programming commodity computer clusters to perform large-scale data processing in a single pass. Hadoop is the most popular open-source implementation of the MapReduce model which provides a simple abstraction for large-scale distributed algorithm; it has become a popular distributed computing and data analysis paradigm in recent years. While, Hadoop MapReduce suits well for embarrassingly parallel problems, it suffers significant troubles when dealing with iterative algorithms; as a consequence, many alternative frameworks that support this class of algorithms were created. In this paper, we propose architecture for such configuration implemented in an SPC (Scientific Private Cloud) prototype, using the Hadoop 2.0 next generation platform to allow the use of alternative programming frameworks respecting a hybrid approach, while retaining the scalability and fault tolerance of Hadoop MapReduce. By adapting scientific problems to execute them in our Scientific Cloud, experiments conducted show the effectiveness of the proposed model and its impact on the ease of frameworks handling.

Keywords: Scientific Cloud, Hadoop next generation, Hybrid approach.

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ABOUT THE AUTHORS

Yassine Tabaa
received in 2005 the computer engineer degree from the National School of Applied Sciences in Tangier, Morocco. Currently, he is a Ph.D Student in the LaSIT Laboratory (Information and Communication Systems Laboratory) at Abdelmalek Essaadi University. His interests focus on Distributed Computing, Cloud Computing and eLearning.

Abdellatif Medouri
studied applied physics at the University of Granada in Spain, he got his Ph.D. in signal processing from the University of Granada, Spain (1995). Currently, he is the vice-head of polydisciplinary faculty and lead of Modeling and Information Theory team. His main research interests include cloud computing and new technologies for education.


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