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Getting started with parallel MCMC « Darren Wilkinson's research blog
http://darrenjw.wordpress.com/2010/12/14/getting-started-with-parallel-mcmc/[12/25/2011 5:10:29 PM]
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Darren Wilkinson's research blog
Statistics, computing, Bayes, stochastic modelling, systems biology and bioinformatics
Getting started with parallel MCMC
Introduction to parallel MCMC for Bayesian inference,
using C, MPI, the GSL and SPRNG
Introduction
This post is aimed at people who already know how to code up
Markov Chain Monte Carlo (MCMC) algorithms in C, but are
interested in how to parallelise their code to run on multi-core
machines and HPC clusters. I discussed different languages for
coding MCMC algorithms in a previous post. The advantage of C is
that it is fast, standard and has excellent scientific library support.
Ultimately, people pursuing this route will be interested in running
their code on large clusters of fast servers, but for the purposes of
development and testing, this really isn’t necessary. A single dual-
core laptop, or similar, is absolutely fine. I develop and test on a
dual-core laptop running Ubuntu linux, so that is what I will
assume for the rest of this post.
There are several possible environments for parallel computing,
but I will focus on the Message-Passing Interface (MPI). This is a
well-established standard for parallel computing, there are many
implementations, and it is by far the most commonly used high
performance computing (HPC) framework today. Even if you are
ultimately interested in writing code for novel architectures such as
GPUs, learning the basics of parallel computation using MPI will be
time well spent.
MPI
The whole point of MPI is that it is a standard, so code written for
one implementation should run fine with any other. There are
many implementations. On Linux platforms, the most popular are
OpenMPI, LAM, and MPICH. There are various pros and cons
associated with each implementation, and if installing on a
powerful HPC cluster, serious consideration should be given to
which will be the most beneficial. For basic development and
testing, however, it really doesn’t matter which is used. I use
OpenMPI on my Ubuntu laptop, which can be installed with a
simple:
Follow
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