Parallelization and Deployment of Big Data Algorithms: The TOREADOR Approach

Abstract

In order to reduce the initial investments needed by small and medium enterprises (SMEs) to acquire the necessary expertise, hardware and software to run proper Big Data Analytics, TOREADOR proposes a Big Data Analytics framework which supports users in devising their own Big Data solutions by keeping the inherent costs at a minimum. Among the objectives of the TOREADOR framework is supporting developers in parallelizing and deploying their algorithms, in order to develop they own analytics solutions. This paper describes the Code-Based approach, developed by CINI and adopted within the TOREADOR framework to parallelize users' algorithms and deploy them on distributed platforms, with a focus on its integration with the web services and resources offered by ATOS for the actual deployment of the solution.