Difference: VirgoComputing (11 vs. 12)

Revision 122010-12-08 - GergelyDebreczeni

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META TOPICPARENT name="WebHome"

Home
What is Virgo ?
People
CBwaves
GPU_inspiral
Computing activities
Analysis activities
Theory
Galery
Publications
Events
Useful links
Getting started
TDK/BSc/MSc/PhD
Archive
Contact
Other GW groups
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  • If you don't have AFS account for our cell contact: gridadm@rmki.kfki.hu
  • If you don't have a digital certificate, please read this.
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<

What we are doing

>
>

GPU machines

  • grid251.kfki.hu,
  • opal4.rmki.kfki.hu

The following GPUs are available:

  • 3 nVidia, GTX 295
  • 3 ATI Radeon 5970
  • 2 nVidia tesla C2050

In case of interest test login accounts can be requested. Please send an e-mail to Gergely.Debreczeni@rmki.kfki.hu

What we are/were doing

 

Virgo data transfer issues

Feasibility study of data transfer from Cascina with Grid tools

Read the description on this page.
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Checksum issues

 

Running analysis pipelins on the EGEE Grid

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<		 Read the implementation plan here
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>		A feasibility study on how to use EGI Grid resources for the execution of gravitational wave search pipelines. Read the implementation plan here.
 

Running CBC analysis pipelins in Bologna computer center

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<		 Read the description here

Testing GPU accelerated CBC pipelines

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>		 The CNAF computer center is part of the EGI Grid, as such its resources can be accessed only through the Grid middleware and Virtual Organisation. The CBC inspiral pipeline software is heavility based on the condor batch system which is not supported and not used by the majority of EGI Grid sites. The goal of this porject is to set up a framewrok which allows the execution of CBC and CW analysis pipelines on Grid resources without modifying the software already in use. Read the description here

Hough-transformation implemented on GPUs

The Hough transformation is used for the search of gravitational waves emitted by rotating neutron stars. The sensitivity of the search is computationally bounded. The goal of this project is to implement and paralellize the algorithm on GPU devices which could possible results a significant improvement of the search sensitivity. Read the description here.
 
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