@inproceedings{f2f47aa1d56d49678cd234d634003fa2,
title = "Dispel4py: A python framework for data-intensive scientific computing",
abstract = "This paper presents dispel4py, a new Python framework for describing abstract stream-based workflows for distributed data-intensive applications. The main aim of dispel4py is to enable scientists to focus on their computation instead of being distracted by details of the computing infrastructure they use. Therefore, special care has been taken to provide dispel4py with the ability to map abstract workflows to different enactment platforms dynamically, at run time. In this work we present four dispel4py mappings: Apache Storm, MPI, multi-threading and sequential. The results show that dispel4py is successful in enacting on different platforms, while also providing scalable performance.",
keywords = "data streaming, Data-intensive computing, e-Infrastructures, programming frameworks, Python, scientific workflows",
author = "Rosa Filguiera and Iraklis Klampanos and Amrey Krause and Mario David and Alexander Moreno and Malcolm Atkinson",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 International Workshop on Data-Intensive Scalable Computing Systems, DISCS 2014 - Held in Conjuction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2014 ; Conference date: 16-11-2014",
year = "2014",
month = apr,
day = "2",
doi = "10.1109/DISCS.2014.12",
language = "English",
series = "Proceedings of DISCS 2014: The 2014 International Workshop on Data-Intensive Scalable Computing Systems - Held in Conjuction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9--16",
booktitle = "Proceedings of DISCS 2014",
address = "United States",
}