Building a Beowulf Cluster/Parallelization of computation

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As the principal goal of having the cluster is to run programs in parallel on different machines, I installed protocols for message-passing for distributed-memory applications. There are two common ones: the Parallel Virtual Machine (PVM) and Message Parsing Interface (MPI).

For scientific computing we can use high-level computing platforms or languages such as C/C++ and fortran. Here we will see GNU R and matlab. R can spawn parallel jobs using either PVM or MPI. Matlab comes with an implementation of MPI (more precisely mpich2).

Note that for PVM you need to enable password-less ssh access (see previous section) from the server to all clients. Also, for PVM, MPI (includes matlab's mdce), the network configuration you have to remove the host names from the loop-back line (where it says of the /etc/hosts file. Just put localhost instead. Then you need a text file with a list of all machines you wish to use for computing and call it pvmhosts and mpihosts.