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GPU-accelerated Parameter Estimation

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Submitted by:
Sadakazu Haino
Updated by:
Sadakazu Haino
Document Created:
19 Jan 2018, 13:26
Contents Revised:
19 Jan 2018, 13:53
DB Info Revised:
16 Mar 2018, 05:46
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Parameter Estimation (PE) is a time-consuming process; we need to find a new way to accelerate it in view of many-GW-detection era towards 3G. A Frequency-domain CBC PE on 15 parameters with Nested sampling with MCMC sub-chains and IMRPhenomPv2 waveform model has been accelerated with GPU by factor of ~100. The codes are all newly written in C++ and CUDA and produce the same output as LALInference for cbcBayesPostProc
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