High-performance astrophysical visualization using Splotch

Z. Jin, Mel Krokos, M. Rivi, C. Gheller, K. Dolag, M. Reinecke

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The scientific community is presently witnessing an unprecedented growth in the quality and quantity of data sets coming from simulations and real-world experiments. To access effectively and extract the scientific content of such large-scale data sets (often sizes are measured in hundreds or even millions of Gigabytes) appropriate tools are needed. Visual data exploration and discovery is a robust approach for rapidly and intuitively inspecting large-scale data sets, e.g. for identifying new features and patterns or isolating small regions of interest within which to apply time-consuming algorithms. This paper presents a high performance parallelized implementation of Splotch, our previously developed visual data exploration and discovery algorithm for large-scale astrophysical data sets coming from particle-based simulations. Splotch has been improved in order to exploit modern massively parallel architectures, e.g. multicore CPUs and CUDA-enabled GPUs. We present performance and scalability benchmarks on a number of test cases, demonstrating the ability of our high performance parallelized Splotch to handle efficiently large-scale data sets, such as the outputs of the Millennium II simulation, the largest cosmological simulation ever performed.
    Original languageEnglish
    Pages (from-to)1775-1784
    Number of pages10
    JournalProcedia Computer Science
    Volume1
    Issue number1
    DOIs
    Publication statusPublished - 31 May 2010

    Keywords

    • visual discovery
    • Splotch
    • numerical simulations
    • high-performance visualization
    • MPI
    • CUDA-enabled GPUs
    • Millenium II simulation

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