(r3) GPU_inspiral < RmiVirgo

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---+ GPU_inspiral

GPU_inspiral is a low-latency, high performance many-core implementation of the matched-filter gravitational wave search algorithm, developed by the RMKI Virgo Group.
The base is an architecture and vendor independent OpenCL code. The sub algorithms implemented so far are the following:

   * template generation
   * PSD calculation
   * matched-filtering
   * chi2 calculation
   * clustering of events

---+ Performance
Performence test was done on a  2048 sec long data chunk, 500 template of 64 sec long was filtered. The code run on an Nvidia Tesla C2050. To produce the SNR time series it took ~17 sec
for =gpu_inpiral=, this has to be compare with the ~40 minutes necessary for =lalapps_inspiral= to produce the same result. 

<center>
---++++!! This results a *speed-up factor of 2 orders of magnitude* ! 
</center>

---+ Documentation
There is some material available on this project:
   * A poster about the project [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/gpu_inspiral_poster.pdf][here]].
   * A summary paper [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/gpu_inspiral_paper.pdf][here]].
   * Bence's Somhegyi MSc thesis (in hungarian) [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/somhegyi-msc.pdf][here]].

   * MSc thesis lecture (in hungarian) [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/somhegyi-msc_slides.pdf][here]].
   * MSc thesis presentation [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/slides_hun.pdf][in hungarian]] and [[http://www.grid.kfki.hu/project/virgo/gpu_inspiral/slides_en.pdf][in english]].

---+ Future plans
Instead of writing up a completely new analysis software we will incorporate the code developed as =gpu_inspiral=
to be part of the [[https://bugs.ligo.org/redmine/projects/pycbc][pyCBC project]].

---+ Developers
   1 Bence Somhegyi 
   1 Gergely Debreczeni

Topic revision: r3 - 2011-06-30 - GergelyDebreczeni

RmiVirgo

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