2 research outputs found

    Parallelizing the XSTAR Photoionization Code

    Full text link
    We describe two means by which XSTAR, a code which computes physical conditions and emission spectra of photoionized gases, has been parallelized. The first is pvm_xstar, a wrapper which can be used in place of the serial xstar2xspec script to foster concurrent execution of the XSTAR command line application on independent sets of parameters. The second is PModel, a plugin for the Interactive Spectral Interpretation System (ISIS) which allows arbitrary components of a broad range of astrophysical models to be distributed across processors during fitting and confidence limits calculations, by scientists with little training in parallel programming. Plugging the XSTAR family of analytic models into PModel enables multiple ionization states (e.g., of a complex absorber/emitter) to be computed simultaneously, alleviating the often prohibitive expense of the traditional serial approach. Initial performance results indicate that these methods substantially enlarge the problem space to which XSTAR may be applied within practical timeframes.Comment: ADASS 2008 (Quebec) proceedings (4 pages, 1 figure

    MPI_XSTAR: MPI-based Parallelization of the XSTAR Photoionization Program

    Full text link
    We describe a program for the parallel implementation of multiple runs of XSTAR, a photoionization code that is used to predict the physical properties of an ionized gas from its emission and/or absorption lines. The parallelization program, called MPI_XSTAR, has been developed and implemented in the C++ language by using the Message Passing Interface (MPI) protocol, a conventional standard of parallel computing. We have benchmarked parallel multiprocessing executions of XSTAR, using MPI_XSTAR, against a serial execution of XSTAR, in terms of the parallelization speedup and the computing resource efficiency. Our experience indicates that the parallel execution runs significantly faster than the serial execution, however, the efficiency in terms of the computing resource usage decreases with increasing the number of processors used in the parallel computing.Comment: 5 pages, 1 figure, accepted for publication in Publications of the Astronomical Society of the Pacific (PASP
    corecore