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As I understand, your ultimate goal is to solve an inverse problem (i.e., infer some parameters from given data / observations). To this end, you want to apply Bayesian Inference, which relates the posterior (i.e., the probability distribution of the unknown parameters) to the likelihood (i.e., the probability model of observing some values given the ...


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I am writing a general answer about porting a program running on a CPU to a GPU or FPGA. Both GPU programs (using say CUDA) and CPU programs are written in high level languages like C, C++. Therefore it is much easier to port a CPU program to its equivalent on a GPGPU. The algorithm that you have presented seems suitable for porting to GPU. It is compute ...


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The previous answer pretty sums up my understanding on this problem. I just want to add 2 solid references on this regard (Both are from an astrophysics context). The paper by Hogg et al provides a pretty hands-on approach while the the survey of Sharma is more of a survey of MCMC analysis usage in astrophysics. I am not from the astrophysics community, but ...


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