Leveraging the Power of Big Data Tools for Large Scale Molecular Dynamics Analysis

Omar A. Mures 1 Emilio J. Padrón 1 Bruno Raffin 2
2 DATAMOVE - Data Aware Large Scale Computing
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : Parallel Molecular Dynamics simulations are generating atom trajectories of growing sizes and complexity. Analyzing these trajectories is expensive computationally and time consuming. One reason is the lack of tools that enable the computational biologist to easily implement the analysis while ensuring reduced processing times exploiting the benefits of parallel architectures. In this paper, we present a comparison between two parallel analytics frameworks based on the Map/Reduce paradigm: HiMach, a dedicated framework for trajectory analysis based on MPI, and Flink, a Big Data analytics framework. Both frameworks enable to hide the complexity of parallel code creation to the programmer, providing significant performance gains compared to a sequential execution.
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Contributor : Bruno Raffin <>
Submitted on : Tuesday, September 18, 2018 - 4:47:46 PM
Last modification on : Thursday, October 11, 2018 - 8:48:05 AM


  • HAL Id : hal-01856367, version 1



Omar A. Mures, Emilio J. Padrón, Bruno Raffin. Leveraging the Power of Big Data Tools for Large Scale Molecular Dynamics Analysis. JP2016 - XXVII Jornadas de Paralelismo, Sep 2016, Salamanca, Spain. pp.1-7. ⟨hal-01856367⟩



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