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GPUinspiral – a low-latency, high-performance implementation of the matched-filter gravitational wave search algorithm

G. Debreczeni, B. Somhegyi
Researh Institute for Particle and Nuclear Physics of the Hungarian Academy of Sciences, 1121, Budapest Konkoly-Thege Miklos u. 29-33 Hungary
RMKI Group, 2011

@article{debreczeni2011gpuinspiral,

   title={GPUinspiral-a low-latency, high-performance implementation of the matched-filter gravitational wave search algorithm},

   author={Debreczeni, G. and Somhegyi, B.},

   year={2011}

}

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A very high performance search pipeline has been developed for the search for gravitational wave signals originating from coalescing compact binary systems in the M<35 MSUN mass range. The goal of this research is to provide a solution to some of the so far computationally unfeasible data analysis methods such as for example the filtering of complete generic double spinning, precessing template banks using the matched-template filtering method, or the filtering of far much longer templates necessary to be used with the advanced gravitational wave detectors. In contrary to previous attempts [1] this implementation allows one to execute the entire analysis algorithms on many-core architectures such as GPUs, and not only a fraction of it which results in a drammatic acceleration of the search algorithm. In a typical inspiral pipeline the a speed-up of 92-fold has been achived using a Tesla C2050 GPU card respect to the reference compared with one core of 3.0 GHz AMD CPU. The features and the current performance of this pipeline are presented.
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