gerald kneller

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  • Massively parallel simulation and analysis of protein structure and dynamics!

    Gerald Kneller!Centre de Biophysique Molculaire, CNRS Orlans, France!

    program Calcul intensif et Simulation

  • Key points!

    !Development of tools for molecular simulation of biological macromolecules on present and future parallel computers!

    ! Interfacing simulation, experiment and theory by improving analysis tools, which rely as well on parallel computing!

    !Both, simulation and analysis are I/O intensive !

  • Partners!

    !Centre de Biophysique Molculaire (CNRS Orlans) : Equipe Biophysique thorique, simulation molculaire et calcul intensif!

    ! Institut Laue-Langevin (Grenoble) : Equipe Computing for Science!

    ! Institut Pasteur (Paris) : Equipe Bioinformatique structurale!

    !Logilab (Paris)!

  • Our existing tools !

    !Molecular Modeling ToolKit (K. Hinsen) for the simulation of biomolecular systems (written in Python + Scientific Python, non-parallel) !!

    !nMoldyn (G. Kneller et al.) : Analysis of MD simulations (version 2, written in Python + Scientific Python + MMTK, non-parallle) !!

  • Simulation engine!

    !Simple and compact C++ code with a flexible communication scheme, which can be adapted to different platforms.!

    !Does only one thing, without knowing details: MD simulation.!

    !Communicates with the outside world via files for system specification and trajectory ourput (HDF5).!

    !Other programs specify the system (for example MMTK) and do the analysis (for example nMoldyn)!

    Konrad Hinsen (CBM), Alexandre Fayolle, Ludovic Aubry (Logilab), Phineus Markwick (ANR/Pasteur)!

  • Implementation!

    ! Simulation engine written in C++.!

    ! Files for system specification (input) and MD trajectories in HDF5 format (with special conventions)!

    ! Communication by MPI or by pipes.!

    ! Energy terms: bonded interactions (bonds, angles, dihedral angles) et non-bonded interactions (Lennard-Jones, Coulomb). !

    ! System specification by MMTK (simulation library in Python/C).!

  • Simulation analysys (nmoldyn)!

    ! 1995 : Version 1(G. Kneller et al.)!

    !! modular FORTRAN 77 code with emphasis on the treatment of MD

    trajectories as large two-dimensional data sets (buffered I/O)!

    !! calculation of quantities relevant for neutron scattering!

    !! Decomposition of simulated spectra through fitted rigid-body motions!

    ! 2003 : Version 2 (T. Rog, K. Murzyn, K. Hinsen, G. Kneller)!

    !! code in Python + Scientific Python + MMTK!

    !! Graphical user interface!

    !! new functions for the development of theoretical models (memory


    History :!

  • nmoldyn 3!! Restructuring the existing code!

    ! New functionalities!

    !! Radial distribution functions, static structure factors (total & partials)!

    !! Rotational correlation functions & parameters of NMR spectroscopy!

    !! Radius of gyration & atomic position fluctuations (dynamics of biomolecules)!

    !! Center-of-mass trajectories, subtraction of global motions (translation & rotation) of macromolecules!

    !! Dynamical analysis of protein secondary structure (ScrewFit)!

    !! Quasi-harmonic analysis!

    !! Visualisation of results!

    ! Parallel computation of certain quantities based on PYRO (task farming through Python remote objects). Parallelisation by atome, q-vector, time frame!

    ! Improved Graphical User interface!

    ! Documentation & test cases !

    ! Available for Linux, MacOS X, Windows!

  • Expore the structure and dynamics of condensed matter at the atomic scale (nm,ns)!

    Incoherent scattering: Averaged single-particle dynamics!

    Coherent scattering : Collective structure and dynamics!

    Example 1 : Neutron scattering!

    Computationally very intensive!!

  • Example 2 : NMR !

    Express NMR relaxation rates in terms of the Fourier spectra of site-specific rotational time correlation functions (e.g. N-H vectors)!

    Global rotation! Internal motions!

  • MD! FFT! MC!



    Molecular system!

    Ideal experimental observable!Real experimental observable!

    Towards the virtual experiment!

  • Challenges for virtual experiments!!Parallel I/O and/or analysis on the fly?!

    ! Integrate the experimental environment!

    ! Integrate heterogeneous data flows and simulation techniques!

    !The P in HPC must consider the sum of all parts of the simulation - performance measurements must include also I/O operations/data flow.!

    !Which level of information hiding can be attained in programming parallel machines?!

  • Merci

    " ! Konrad Hinsen, CBM Orlans/SOLEIL

    " ! Vania Calandrini, CBM Orlans/SOLEIL

    " ! Paolo Calligari, CBM Orlans/SOLEIL

    " ! Vronique Hamon, CBM Orlans

    " ! Daniel Abergel, ENS Paris

    " ! Marie-Claire Bellissent, LLB CEA Saclay

    " ! Dietmar Paschek, Univ. Dortmund

    programme Calcul intensif et Simulation