Building high-performance clusters with LAM/MPI
Nowadays, a large number of commercial applications, especially in the areas of engineering, data mining, scientific/medical research, and oil exploration, are based on the capabilities of parallel computing. In most cases, programmers must design or customize these parallel applications to benefit from the possibilities of the parallel architecture. Message-Passing Interface (MPI) is a set of API functions that pass messages between processes (even between processes that are running on different physical servers) so a program can operate in a completely parallel fashion. MPI has now become a standard in the parallel programming world.
LAM/MPI [1] is an open source implementation of the MPI standard maintained by students and faculty at Indiana University. The LAM/MPI system has been around for 20 years, and it is considered a stable and mature tool. According to the website, LAM/MPI is now in "maintenance mode," with most of the new development work occurring instead on the alternative next-generation Open MPI implementation. However, LAM/MPI is still receiving critical patches and bug fixes, and the large install base of LAM/MPI systems around the world means that developers who specialize in parallel programming are still quite likely to encounter it.
In addition to offering the necessary libraries and files to implement the mandated MPI API functions, LAM/MPI also provides the LAM run-time environment. This run-time environment is based on a user-level daemon that provides many of the services required for MPI programs.
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