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

Jorji Nonaka; Masahiro Fujita; Kenji Ono

doi:10.15748/jasse.2.108

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

Jorji Nonaka, Masahiro Fujita, Kenji Ono

Research output: Contribution to journal › Article › peer-review

Abstract

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 language	English
Pages (from-to)	108-125
Number of pages	18
Journal	JASSE
Volume	2
Issue number	1
DOIs	https://doi.org/10.15748/jasse.2.108
Publication status	Published - 2015

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abstract = "Large-scale numerical simulations on modern leading-edge supercomputers have been continuously generating tremendous amount of data. In-Situ Visualization 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 Multi-Step Image Composition 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.",

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

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