FAMAD

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== Short Description ==
== Short Description ==
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''Tobefilledin''
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''FAMAD is a collection of algorithms to compute different fractal parameters for mass distribution. This type of algorithms are highly parallizable and can analyse large data customary on clusters. The input data will be high resolution images in the most used format in astrophysics, FITS. The application will use a box counting algorithm running on GPU (with CUDA), for the determination of fractal dimension. Data analysis and ploting will be done in ROOT Framework.''
== Problems Solved ==
== Problems Solved ==
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''Tobefilledin''
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''Fractal algorithms are generally highly parallelizable. This application implements  different algorithms on GPU (such as box counting, fractal lacunarity and correlation length)  for fractal study. Due to the architecture of the graphical processors, the application will run simulatatiously thousands of threads in parallel. Thus, fractal analysis will be much faster than on CPU.''
== Scientific and Social Impact ==
== Scientific and Social Impact ==
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''Tobefilledin''
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''General scientific image on the formation and evolution of the galaxies is that they formed by gravitational collapse of matter. The study of the fractal mass distribution of spiral galaxies will shade new light on the formation and evolution of galaxies. The application will provide new data of spiral arms and their fractalness.
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We hope that at the end of this study, the general scientific view of the formation and evolution of spiral galaxies will change radically.
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''
== Collaborations and Beneficiaries ==
== Collaborations and Beneficiaries ==
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''Tobefilledin''
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''Computational astrophysics.''
== Technical Features and HP-SEE Implementation ==
== Technical Features and HP-SEE Implementation ==
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* Primary programming language: ''Tobefilledin''
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* Primary programming language: ''C++''
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* Parallel programming paradigm: ''Tobefilledin''
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* Parallel programming paradigm: ''GPGPU''
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* Main parallel code: ''Tobefilledin''
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* Main parallel code: ''CUDA''
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* Pre/post processing code: ''Tobefilledin''
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* Pre/post processing code: ''CUDA''
* Application tools and libraries: ''Enumerate (comma separated)''
* Application tools and libraries: ''Enumerate (comma separated)''
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* Number of cores required: ''Tobefilledin''
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* Number of cores required: ''4x480 GPUs, 32 CPUs''
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* Minimum RAM/core required: ''Tobefilledin''
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* Minimum RAM/core required: ''1.5GB/video card, 2GB/core''
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* Storage space during a single run: ''Tobefilledin''
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* Storage space during a single run: ''100MB''
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* Long-term data storage: ''Tobefilledin''
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* Long-term data storage: ''1TB''
== Usage Example ==
== Usage Example ==

Revision as of 05:42, 5 July 2011

Contents

General Information

  • Application's name:
  • Virtual Research Community: VRC Name
  • Scientific contact: Name Surname, e-mail
  • Technical contact: Name Surname, e-mail
  • Developers: Group, department, institution, country
  • Web site: http://tobefilledin/

Short Description

FAMAD is a collection of algorithms to compute different fractal parameters for mass distribution. This type of algorithms are highly parallizable and can analyse large data customary on clusters. The input data will be high resolution images in the most used format in astrophysics, FITS. The application will use a box counting algorithm running on GPU (with CUDA), for the determination of fractal dimension. Data analysis and ploting will be done in ROOT Framework.

Problems Solved

Fractal algorithms are generally highly parallelizable. This application implements different algorithms on GPU (such as box counting, fractal lacunarity and correlation length) for fractal study. Due to the architecture of the graphical processors, the application will run simulatatiously thousands of threads in parallel. Thus, fractal analysis will be much faster than on CPU.

Scientific and Social Impact

General scientific image on the formation and evolution of the galaxies is that they formed by gravitational collapse of matter. The study of the fractal mass distribution of spiral galaxies will shade new light on the formation and evolution of galaxies. The application will provide new data of spiral arms and their fractalness. We hope that at the end of this study, the general scientific view of the formation and evolution of spiral galaxies will change radically.

Collaborations and Beneficiaries

Computational astrophysics.

Technical Features and HP-SEE Implementation

  • Primary programming language: C++
  • Parallel programming paradigm: GPGPU
  • Main parallel code: CUDA
  • Pre/post processing code: CUDA
  • Application tools and libraries: Enumerate (comma separated)
  • Number of cores required: 4x480 GPUs, 32 CPUs
  • Minimum RAM/core required: 1.5GB/video card, 2GB/core
  • Storage space during a single run: 100MB
  • Long-term data storage: 1TB

Usage Example

Tobefilledin, text and (maybe) images.

Publications

  • ...
  • ...
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