Keywords: user_guide

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## 3.1 Understanding Parallelism

Two different parallelization paradigms are currently implemented in QUANTUM ESPRESSO:

1. Message-Passing (MPI). A copy of the executable runs on each CPU; each copy lives in a different world, with its own private set of data, and communicates with other executables only via calls to MPI libraries. MPI parallelization requires compilation for parallel execution, linking with MPI libraries, execution using a launcher program (depending upon the specific machine). The number of CPUs used is specified at run-time either as an option to the launcher or by the batch queue system.
2. OpenMP. A single executable spawn subprocesses (threads) that perform in parallel specific tasks. OpenMP can be implemented via compiler directives (explicit OpenMP) or via multithreading libraries (library OpenMP). Explicit OpenMP require compilation for OpenMP execution; library OpenMP requires only linking to a multithreading version of mathematical libraries, e.g.: ESSLSMP, ACML_MP, MKL (the latter is natively multithreading). The number of threads is specified at run-time in the environment variable OMP_NUM_THREADS.

MPI is the well-established, general-purpose parallelization. In QUANTUM ESPRESSO several parallelization levels, specified at run-time via command-line options to the executable, are implemented with MPI. This is your first choice for execution on a parallel machine.

Library OpenMP is a low-effort parallelization suitable for multicore CPUs. Its effectiveness relies upon the quality of the multithreading libraries and the availability of multithreading FFTs. If you are using MKL,1you may want to select FFTW3 (set `CPPFLAGS=-D__FFTW3...` in `make.sys`) and to link with the MKL interface to FFTW3. You will get a decent speedup ( 25%) on two cores.

Explicit OpenMP is a recent addition, still under development, devised to increase scalability on large multicore parallel machines. Explicit OpenMP can be used together with MPI and also together with library OpenMP. Beware conflicts between the various kinds of parallelization! If you don't know how to run MPI processes and OpenMP threads in a controlled manner, forget about mixed OpenMP-MPI parallelization.

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