scientific computer

computer, server for scientific computing
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 07/10/13
  • Minor correction: 07/10/13
  • Index card author: Luc Hogie (I3S)
  • Theme leader : Dirk Hoffmann (Centre de Physique des Particules de Marseille (CPPM-IN2P3))

jaseto : JAva SErialisation TOolkit

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 2013.08.30.14.13.40 - 2013.08.30
  • License(s): LGPL
  • Support: maintained, ongoing development
  • Designer(s): Luc Hogie
  • Contact designer(s): luc.hogie@cnrs.fr
  • Laboratory, service:

 

General software features

Jaseto is a Java library enabling the description of Java objects in XML, and conversely, the creation of Java object from their XML description. This process is commonly referred to as (de)serialization or (un)marshalling. It is usually employed to make the data persistent across executions, by storing the XML text on disk or into XML databases.

Other libraries such as XStream, Castor, and JAXB are other viable solutions. Compared to these, Jaseto offers a cleaner and shorter source code, better performance (its proves 10× faster than Castor and XStream), a solution to some of their limitations: no need to know in advance the type of an object to be deserialized, no need to resort to annotations, no need to follow the JavaBean spec, etc.

Context in which the software is used

Jaseto is used in our lab in order to store and export graph and configuration data.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 21/02/13
  • Minor correction: 22/02/13

GammaLib : C++ library for gamma-ray astronomy data analysis

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 00-07-00 - 11 January 2013
  • License(s): GPL - Version 3
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): Jürgen Knödlseder
  • Contact designer(s): jurgen.knodlseder@irap.omp.eu
  • Laboratory, service: DESY (Deutsches Elektronen-Synchrotron, Hamburg), MPIK (Max-Planck Institute for Nuclear Physics, Heidelberg)

 

General software features

GammaLib is a self-contained, instrument independent, open source, multi-platform C++ library, that implements all code required for high-level science analysis of astronomical gamma-ray data. GammaLib is also wrapped into a Python module.

GammaLib does not rely on any third-party software, except of HEASARC's cfitsio library that is used to implement the FITS interface. Large parts of the code treat gamma-ray observations in an abstract representation, and do neither depend on the characteristics of the employed instrument, nor on the particular formats in which data and instrument response functions are delivered. Instrument specific aspects are implemented as isolated and well defined modules that interact with the rest of the library through a common interface. This philosophy also enables the joint analysis of data from different instruments, providing a framework that allows for consistent broad-band spectral fitting or imaging.

GammaLib contains the following modules:

  • a module for observation, data and instrument response function handling
  • a module for the definition of models (astrophysical source and background models)
  • a module for model fitting
  • a module for image handling
  • a module for the creation of ftools
  • a module for numerical computations
  • a module for linear algebra
  • a module with support functions for GammaLib classes
  • an interface for handling of FITS data
  • an interface for handling data in XML format
  • an interface for handling IRAF parameters

GammaLib is highly portable, requiring only a C++ compiler for building. The only dependency needed for operations is the cfitsio library that implement the FITS interface. If available, GammaLib can also benefit from an OpenMP support to perform parallel computations on multi-processor or multi-core machines.

All GammaLib functionalities are accessible via a C++ interface. GammaLib is also available as a Python module (version 2 and 3).

To enable the data analysis for a specific telescope, a dedicated module needs to be implemented that describes the format and the structure of the telescope's data, as well as its instrument response function. By default, GammaLib supports analysis of data from the Fermi/LAT telescope, the COMPTEL telescope, existing Cherenkov telescopes (H.E.S.S., MAGIC, VERITAS), and the future Cherenkov Telescope Array (CTA).

Context in which the software is used

GammaLib is used as basis of the ctools software, a set of executables that is proposed as the science analysis framework for the Cherenkov Telescope Array (CTA) project.

GammaLib is also employed for the analysis of Fermi/LAT data.

Publications related to the software

Knödlseder, J. 2011, GammaLib - A new framework for the analysis of Astronomical Gamma-Ray Data, submitted to arXiv (http://arxiv.org/abs/1110.6418)

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 02/08/12
  • Minor correction: 02/08/12

Stratuslab : complete IaaS cloud distribution

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: v2.0 - 25 June 2012
  • License(s): Other - Apache-2, AGPL
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): StratusLab Collaboration (CNRS, UCM, GRNET, SixSq, TID, et TCD)
  • Contact designer(s): support@stratuslab.eu
  • Laboratory, service: Universidad Complutense de Madrid (Madrid, Spain), GRNET (Athens, Greece), SixSq (Geneva, Switzerland), Telefónica I+D (Madrid, Spain), Trinity College Dublin (Dublin, Irland)

 

General software features

logo stratuslab
The distribution contains all of the necessary for deploying an Infrastructure-as-a-Service (IaaS) cloud: network, storage, and virtual machine management. Moreover, it provides innovative features like the Marketplace that facilitates sharing of virtual appliances, service management that allows deployment and autoscaling of multi-machine services, and support for multi-cloud scenarios. The distribution supports multiple operating systems (CentOS 6.2, Fedora16, and OpenSuSE 12.1) and is ideal for both public and private cloud deployments. The StratusLab client, written in Python, provides a simple command line interface to access to StratusLab cloud infrastructures from GNU/Linux, Mac OS X, and Windows machines.

Source code for the distribution can be found on GitHub.

Context in which the software is used

StratusLab is used at LAL to provide one of the StratusLab reference cloud infrastructures, a public cloud open to anyone for non-commercial use. The other StratusLab reference cloud is operated by GRNET in Greece. LAL also operates a second, private cloud infrastructure for deployment of laboratory services; existing services are gradually being migrated to this cloud infrastructure.

CNRS/IBCP operates a StratusLab cloud to support bioinformatics research and services. This public cloud infrastructure is available to users of the ReNaBi network. A portal, customized for bioinformatics users, facilitates use of the IBCP cloud and simplifies access to relevant virtual appliances and databases.

There are also commercial deployments of the StratusLab cloud distribution that support software engineering processes (such as deployment of ESA's SCOS-2000 platform) and scientific use (like the Atos Helix Nebula cloud infrastructure).

Publications related to the software

All of the related publications of the project are available from :

The chapter of the book "European Research Activities in Cloud Computing" contains a general description of the StratusLab project and its cloud distribution.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 18/07/12
  • Minor correction: 28/05/14

Morse : Generic simulator for robotics

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 1.2 - january 2014
  • License(s): BSD
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): Main developers: Arnaud Degroote (LAAS-CNRS), Gilberto Echeverria (LAAS-CNRS), Michael Karg (TUM), Séverin Lemaignan (LAAS-CNRS). See the full list.
  • Contact designer(s): morse-dev AT laas DOT fr
  • Laboratory, service: Technische Universität München (TUM) full list

 

General software features

MORSE is a generic simulator for academic robotics. It focuses on realistic simulation of small to large environments, indoor or outdoor, with one to over a dozen of autonomous robots. It provides a set of standard sensors (cameras, laser scanner, GPS, odometry,...), actuators (speed controllers, high-level waypoints controllers, generic joint controllers) and robotic bases (ATRV, generic 4 wheel vehicle, PR2,...) used in robotics research laboratories. New components can easily be added.

Morse can use and test software components interacting through several middlewares used in robotics, including: Fiche Plume pocolibs, yarp and ROS.

One of the main design choice for MORSE is the ability to control the degree of realism of the simulation, form photo-realistic rendering for image processing to semantic levels, avoiding heavy processing to extract information.

Morse is based on the Fiche Plume Blender modelling and real-time 3D rendering environment and on the Bullet physics simulator engine.

Context in which the software is used

Academic research in robotics, development and debugging of software components, teaching,...

Publications related to the software
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 03/01/12
  • Minor correction: 03/01/12

XtremWeb-HEP : middleware for distributed data processing

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 7.6.4 - 12/12/2011
  • License(s): GPL
  • Status: validated (according to PLUME)
  • Support: maintained, ongoing development
  • Designer(s): Oleg LODYGENSKY
  • Contact designer(s): xtremweb (at) lal.in2p3.fr
  • Laboratory, service:

 

General software features
  • ’XtremWeb-HEP’ is a middleware for Distributed Data Processing (grids) :
    –  It permits Administrators to :
        - manage various Users and Applications, by providing adequate access rights to them,
        - catalog various Data and Computing Resources :
           Â· PC farms managed by an IT department,
           Â· PC grids contributed by volunteer citizens,
    –  It permits Users to submit Jobs referencing these Applications,
    –  From Job descriptions, it dynamically deploys and executes these Applications on available Computing Resources, then it provides the results to authorized Users,
    –  It protects the Computing Resources running Mac OS X by starting the Application inside MAC OS X Sandbox,
    –  For the access to data, it permits the usage of HTTP, HTTPS, and any URI scheme whose driver is provided by the User.

Secured three tiers Architecture.  Scheduler and data repository managed by a software administrator on a server;  Client installed on the machine of each User (for ex. scientist);  Worker installed on the resource of each contributor.

  • Soon will come in production the version of XtremWeb-HEP additionally managing the submission of complete virtual machines for execution inside VirtualBox.

  • Interoperability with other grid middleware stacks :
    –  XtremWeb-HEP accepts X509 certificates and proxies for user management, in particular those of the DEGISCO international project.
    –  XtremWeb-HEP integrates a bridge permitting suitable XtremWeb-HEP jobs to be accepted by the gLite middleware in order to be executed by the EGI European infrastructure.
    –  On the other way, thanks to the 3G Bridge of the EDGI European project, the resources gathered by XtremWeb-HEP are available for the many users of the EGI infrastructure (gLite, ARC and Unicore middleware stacks).

  • Domain, Infrastructures, Documentation and Maintenance :
    –  In spite of its name, XtremWeb-HEP is used way beyond High Energy Physics :  Biology,  ADN Research,  Mathematics,  Physics of Solids,  Signal Processing.
    –  XtremWeb-HEP is powering at least 2 production grids (For each grid, look at the 'Statistics' page) :
        - http://www.xtremweb-hep.org/lal/xw_lal/
        - http://xw.lri.fr:4330/XWHEP
    –  XtremWeb-HEP has a complete up to date set of user manuals, presented at http://www.xtremweb-hep.org/spip.php?rubrique16
    –  XtremWeb-HEP is maintained by the software team presented at http://www.xtremweb-hep.org/spip.php?rubrique35 and is strongly supported by Institut des Grilles et du Cloud, INRIA, ENS Lyon, GRID5000

Context in which the software is used
  • Distributed Data Processing
  • Distributed Computing
  • Resource Sharing
  • Computing Grid (PC Grid)
  • Job Submission
Publications related to the software
  • Hybrid Distributed Computing Infrastructure Experiments in Grid5000 : Supporting QoS in Desktop Grids with Cloud Resources   http://users.lal.in2p3.fr/lodygens/gc/g5k.pdf
    G. Fedak, S. Delamare, O. Lodygensky.   Grid 5000 School, Reims, France - April 18-21, 2011

  • Extending the EGEE grid with XtremWeb-HEP Desktop Grid   http://users.lal.in2p3.fr/lodygens/gc/PCGrid2010.pdf
    H. He, G. Fedak, P. Kacsuk, Z. Farkas, Z. Balaton, O. Lodygensky, E. Urbah, G. Caillat, F. Aurajo, A. Emmen.   4th Workshop on Desktop Grids and Volunteer Computing Systems, Melbourne, Australia - May 17-20, 2010

  • EDGeS : Bridging EGEE to BOINC and XtremWeb   http://users.lal.in2p3.fr/lodygens/gc/EDGeS-Bridgi...
    E. Urbah, P. Kacsuk, Z. Farkas, G. Fedak, G. Kecskemeti, O. Lodygensky, A. Marosi, Z. Balaton, G. Caillat, G. Gombas, A. Kornafeld, J. Kovacs, H. He, and R. Lovas.   JoGC Journal of Grid Computing, Volume 7, Number 3, 2009.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 14/12/11
  • Minor correction: 07/09/13

pyFAI : azimuthal integration for 2D detectors

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 0.9.0 - July 30; 2013
  • License(s): GPL
  • Status: stable release
  • Support: maintained, ongoing development
  • Designer(s): Jérôme Kieffer (Python code), Dimitris Karkoulis (OpenMP & OpenCL), Peter Bösecke (Geometry), V. Armando Solé (Image processing), Manuel Sánchez del Río (Original idea), Jonathan P. Wright (Ideas), Frédéric Emmanuel Picca (Documentation and ideas)
  • Contact designer(s): Jerome.Kieffer@esrf.fr
  • Laboratory, service:

 

General software features

PyFAI is a Python library for azimuthal integration; it allows the conversion of diffraction images taken with 2D detectors like CCD cameras into X-Ray powder patterns that can be used by other software like Rietveld refinement tools (i.e. FullProf), phase analysis or texture analysis.

As PyFAI is a library, its main goal is to be integrated in other tools like PyMca or EDNA. To perform online data analysis, the precise description of the experimental setup has to be known. This is the reason why PyFAI includes geometry optimization code working on "powder rings" of reference samples. Alternatively, PyFAI can also import geometries fitted with other tools like Fit2D.

PyFAI has been designed to work with any kind of detector with any geometry (transmission, reflection, off-axis, ...). It uses the Python library Fabio to read most images taken by diffractometer (Fabio officially supports 12 manufacturers and 20 different image formats).

Context in which the software is used

2D detectors (CCD, CMOS or pixel detectors, ...) have progressively replaced punctual detectors over the 15 last years in the world of diffraction (single crystal, powder diffraction WAXS or small angle scattering SAXS). Those detectors, with wide sensitive area, have spatial resolution of dozens of microns and provide millions of pixels. PyFAI can be used on SAXS and WAXS data to reduce them into 1D (azimuthal integration) or 2D (transformation known as caking).

In order to transform detector images into data to be used by scientists it is necessary to:

  • subtract dark current (correction for the read-out noise)
  • divide by flat-field (correction for the relative sensitivity of pixels or scintillator inhomogeneities)
  • correct for the pixel position (defects of the optical fiber taper)
  • mask out dead pixels
  • convert pixel position from Cartesian space (x,y) to Polar space (2theta, chi)

PyFAI is able to compute all those corrections. Special care has been taken to conserve intensity and surface density by pixel splitting during the re-binning process (which is close to a histogram, but with pixel splitting). The algorithm used is implemented in numpy to provide a bullet-proof version, but faster and more precise version have been implemented in Cython and in OpenCL to achieve best performances with modern graphic cards.

An additional piece of software allows a fast and reliable calibration of the geometry of the experimental setup; allowing online analysis of the data.

Publications related to the software
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 25/10/10
  • Minor correction: 28/10/10

EDNA : framework for plugin-based applications for online data analysis

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 1.0 (Application MXv1 june 2009) - revision SVN 1930
  • License(s): GPL -

    EDNA kernel and many plugins are LGPLv3+

    EDNA applications (like MXv1) and some plugins are GPLv3+

  • Status: stable release, internal use, under development
  • Support: maintained, ongoing development
  • Designer(s):

    Executive Committee Chair: Andrew Leslie (MRC-LMB)

    Project Manager: Olof Svensson (ESRF)

    Project Coordinator: Alun Ashton (Diamond)

    Currently around 10 developers but 40 people have been involved in the project.

  • Contact designer(s): edna-support@esrf.fr
  • Laboratory, service: DLS, MRC-LMB, CCP4, Bessy (HZB), Max Lab. NSLS, SLS-PSI, Univ Sydney, Univ York, Global Phasing

 

General software features

Platform
The EDNA kernel runs on all platforms which can provide a Python interpreter. The MXv1 application runs on all Unix/Linux platforms that have bash, Python (version 2.5 and later) and which can run the programs MOSFLM, LABELIT, RADDOSE and BEST. The EDNA framework and MXv1 application are installed and regularly used at the Diamond Light Source (Didcot), EMBL Hamburg, ESRF Grenoble and NSLS Brookhaven National Laboratory (New York).

EDNA-based applications are designed and developed with the aim of being easily configurable, extensible and smoothly maintainable. This has been made possible thanks to the technical facilities that the EDNA framework provides, including configuration facilities, a library of re-usable components, datamodel-driven code generation machinery and a testing framework.

Modularity
The components are organized in a logical class hierarchy that makes it straightforward to develop new functional plugins by deriving them from the appropriate parent. Two families of plugins have been designed: the first branch contains the execution plugins (EDPluginExec classes) that are responsible for the execution of a particular action (e.g. execution of third-party software); the second branch contains the control plugins (EDPluginControl classes) that are responsible for the data flow (propagation of the data), the workflow (sequential or parallel execution of appropriate execution plugins) and the error-tracking mechanism (propagation of the errors).

Datamodel
The EDNA kernel provides a data model tool kit that allows the construction of elaborate data models needed by advanced applications. In addition, it allows the design of unitary data models that can be unit-tested, so that a plugin can be launched and tested independently of any application context. This tool kit consists of generic low-level class definitions including general types (XSDataString, XSDataFloat etc.) and X-ray experiment classes which can be re-used when designing specific components data models. It is available in several standard data formats including XMI (XML metadata interchange) and XSD (XML schema definition) in order to facilitate importing into UML (unified modeling language) data modeling tools and/or XSD files. The framework also provides (external) code generation machinery generateDS that allows automatic code generation from UML diagrams to Python code via XSD format.

Testing framework
A testing framework has been developed and integrated with the kernel in order to test the applications and the components easily and efficiently. To ensure the reliability and robustness of the components, the testing framework provides all the necessary utilities to check a class (EDTestCase) and a plugin (EDTestCasePlugin) either in a unitary manner (EDTestCasePluginUnit) or by testing its execution in an application context (EDTestCasePluginExecute). These families of tests can be automatically launched via test suites. An automatic analysis of the test results is performed by comparing the obtained result with the expected one (assert mechanism), so that a successful test proves that a result conforms to the expectation. This allows a high degree of confidence when implementing new components or re-implementing features of existing components.

Configuration facilities
Each plugin is configured (path of the controlled executable, batch queuing system configuration, ...) by the mean of XML files. The configuration is selected according to the EDNA_SITE environment variable.

Context in which the software is used

EDNA is used to create online data analysis applications on synchrotron beam-lines (but not only), among them:

  • Mxv1 application for fast characterization of protein crystals; in regular use at the ESRF, the DLS and the NSLS.
  • MXv2 application is in preparation to take advantage of kappa goniostats.
  • Dimple application has been written by CCP4 for doing molecular replacement and ligand location in proteins.
  • Diffraction computed tomography application with azimuthal integration and online sinogram generation with dynamic region of interest for Nano-Analysis Beamlines.
  • Saxs pre-processing (azimuthal integration and averaging) and downstream processing for BioSaxs Beamline.
  • A Tutorial for Raw digital camera development that explains how to take advantage of the parallel capabilities of EDNA.
Publications related to the software

EDNA: a framework for plugin-based applications applied to X-ray experiment online data analysis
M.-F. Incardona, G. P. Bourenkov, K. Levik, R. A. Pieritz, A. N. Popov and O. Svensson
J. Synchrotron Rad. (2009). 16, 872-879 [ doi:10.1107/S0909049509036681 ]

Abstract: EDNA is a framework for developing plugin-based applications especially for online data analysis in the X-ray experiments field. This article describes the features provided by the EDNA framework to ease the development of extensible scientific applications. This framework includes a plugins class hierarchy, configuration and application facilities, a mechanism to generate data classes and a testing framework. These utilities allow rapid development and integration in which robustness and quality play a fundamental role. A first prototype, designed for macromolecular crystallography experiments and tested at several synchrotrons, is presented.

Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 16/08/10
  • Minor correction: 01/06/11

CiGri : lightweight computing grid

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 1.3 - Aout 2009
  • License(s): GPL - v2
  • Status: validated (according to PLUME), stable release, under development
  • Support: maintained, ongoing development
  • Designer(s): Bruno Bzeznik, Nicolas Capit, Olivier Richard, Elton Nicoletti Mathias, Yiannis Georgiou, and various contributors (internships, google summer of code)
  • Contact designer(s): Bruno.Bzeznik@imag.fr
  • Laboratory, service: CIMENT (University of Grenoble Computing center)

 

General software features

The CiGri software allows to set up a grid center to exploit a pre-existing set of super-computers. It is specialised on the management of "bag-of-tasks" jobs. It gathers the unused computing resources from an intranet infrastructure and makes it available for large set of tasks.

More information (in French) at fiche logiciel Fiche Plume.

Context in which the software is used

CiGri software is used at the computing center at Joseph Fourier University of Grenoble (CIMENT) since 2002.

Publications related to the software
  • Yiannis Georgiou, Olivier Richard, et Nicolas Capit.
    Evaluations of the lightweight grid cigri upon the grid5000 platform. In E-SCIENCE '07: Proceedings of the Third IEEE International Conference on e-Science and Grid Computing, pages 279-286, Washington, DC, USA, 2007. IEEE Computer Society.
  • Yiannis Georgiou, Nicolas Capit, Bruno Bzeznik, et Olivier Richard.
    Simple, fault tolerant, lightweight grid computing approach for bag-of-tasks applications. 3rd EGEE User Forum, 2008.
    http://indico.cern.ch/contributionDisplay.py?contr....
  • Yvan Calas, Nicolas Capit, et Estelle Gabarron.
    Cigri : Expériences autour de l’exploitation d’une grille légère. JRES, 2005.
    http://2005.jres.org/paper/90.pdf.
  • F. Dupros, F. Boulahya, J. Vairon, P. Lombard, N. Capit, et J-F. Méhaut.
    Iggi, a computing framework for large scale parametric simulations: Application to uncertainty analysis with toughreact. TOUGH Symposium, 2006.
    http://esd.lbl.gov/TOUGHsymposium/pdf/Dupros_IGGI.pdf.
  • J. Aoun, V. Breton, L. Desbat, B. Bzeznik, M. Leabadand, et J. Dimastromatteo.
    Validation of the Small Animal Biospace Gamma Imager Model Using GATE Monte Carlo Simulations on the Grid. In J. Montagnat S. D. Olabarriaga, D. Lingrand, editor, Proceedings of MICCAI-Grid Workshop Medical imaging on grids: achievements and perspectives, MICCAI-Grid Workshop, New York États-Unis d'Amérique, 2008.
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 15/02/10
  • Minor correction: 31/03/10

Giac/Xcas : the swiss knife for mathematics

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 0.8.5 (stable), 0.9.0 (developpement) - 2/2/2010
  • License(s): GPL - GPL 3
  • Status: validated (according to PLUME), stable release
  • Support: maintained, ongoing development
  • Designer(s): Bernard Parisse (code), Renée De Graeve (documentation)
  • Contact designer(s): bernard.parisse@ujf-grenoble.fr
  • Laboratory, service:

 

General software features
  • Giac is a C++ library for computer algebra. It is build on C and C++ libraries: PARI, NTL (arithmetic), CoCoA (Groebner basis), GSL (numerics), GMP (big integers), MPFR (bigfloats) and provides algorithms for basic polynomial operations (product, GCD) and symbolic computations (simplifications, limits/series, symbolic integration, sommation, ...). The library can be configured to accept Maple or TI syntax to ease the transition for users of these systems.
  • Xcas is a GUI application interfaced with Giac. It was first a GUI for symbolic computation, then several modules were added: 2-d and 3-d graphics, dynamic 2-d and 3-d geometry (exact or numeric), spreadsheet, programming environment
Context in which the software is used
  • The giac library is the computing kernel of Xcas online and of the CmathOOCas OpenOffice plugin.
  • Xcas is one of the software available for the French agrégation de maths Fiche Plume. Xcas is also used at the University of Grenoble (undergraduate level).
  • Xcas is one of the softwares used by math teachers in French secondary schools, especially for teaching algorithmic. It has been recently translated in Greek and might also be used in Greek secondary schools.
  • giac (commandline interface) is the computing kernel of some LaTeX tools for math teachers in secondary schools (professor, tablor, pgiac).
Higher Edu - Research dev card
Development from the higher education and research community
  • Creation or important update: 13/02/10
  • Minor correction: 22/03/10

Stochastic Downscaling Method : downscaling stochastic method for computational fluid dynamics

This software was developed (or is under development) within the higher education and research community. Its stability can vary (see fields below) and its working state is not guaranteed.
  • Web site
  • System:
  • Current version: 0.5 - Janvier 2010
  • Status: under development
  • Support: maintained, ongoing development
  • Designer(s): F. Bernardin, M. Bossy, C. Chauvin and A. Rousseau
  • Contact designer(s): Antoine Rousseau (Mail, personal page)
  • Laboratory, service: CETE (Clermont-Ferrand)

 

General software features

This software is written in Fortran95. It is aimed to be used as a downscaling module for an existing software, as for example for a numerical weather forecaster. The inputs of SDM are :

  • the volume of interest (3D domain, for example an embedded sub-domain of an existing one)
  • the desired resolution inside this volume
  • the 3D velocity field of the fluid at the boundary of the domain
  • optional : other physical quantities if the model carries more than the 3D velocity (temperature, salinity, etc.)

The outputs are the fluid velocity (and other fields, depending on the inputs), inside the 3D domain, at the desired resolution, together with the turbulent kinetic energy.

Context in which the software is used

This software is a research tool that is made to compare probabilistic Langevin models to traditional techniques of mesh refinement (AMR, etc.). It is developed both by TOSCA and MOISE project-teams at INRIA, and is aimed to be used by the developers, together with a few physicists from the dynamic meteorology lab (LMD, Paris) for its validation on real cases.

Publications related to the software

The following publications are associated to SDM:

  • F. Bernardin, M. Bossy, C. Chauvin, J-F. Jabir, A. Rousseau

    Stochastic Lagrangian Method for Downscaling Problems in Computational Fluid Dynamics. Submitted, 2010.

  • F. Bernardin, M. Bossy, C. Chauvin, P. Drobinski, A. Rousseau and T. Salameh.

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