Multi-Step Image Composition Approach for Sort-Last Massively Parallel Rendering

Jorji Nonaka, Masahiro Fujita, Kenji Ono

    Research output: Contribution to journalArticlepeer-review


    Large-scale numerical simulations on modern leading-edge supercomputers have been continuously generating tremendous amount of data. <i>In-Situ Visualization</i> is widely recognized as the most rational way for analysis and mining of such large data sets by the use of sort-last parallel visualization. However, sort-last method requires communication intensive final image composition and can suffer from scalability problem on massively parallel rendering and compositing environments. In this paper, we present the <i>Multi-Step Image Composition</i> approach to achieve scalability by minimizing undesirable performance degradation on such massively parallel rendering environments. We verified the effectiveness of this proposed approach on K computer, installed at RIKEN AICS, and achieved a speedup of 1.8× to 7.8× using 32,768 composition nodes and different image sizes. We foresee a great potential of this method to meet the even larger image composition demands brought about by the rapid increase in the number of processing elements on modern HPC systems.
    Original languageEnglish
    Pages (from-to)108-125
    Number of pages18
    Issue number1
    Publication statusPublished - 2015


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