234Compositor: A flexible parallel image compositing framework for massively parallel visualization environments

摘要

Leading-edge HPC systems have already been generating a vast amount of time-varying complex data sets, and future-generation HPC systems are expected to produce much higher amounts of such data, thus making their visualization and analysis a much more challenging task. In such scenario, theIn-situvisualization approach, where the same HPC system is used for both numerical simulation and visualization, is expected to become more a necessity than an option. On massively parallel environments, theSort-lastapproach, which requires final image compositing, has become thede factostandard for parallel rendering. In this work, we present the234Compositor, a scalable and flexible parallel image compositor framework for massively parallel rendering applications. It is composed of a single-stage power-of-two conversion mechanism based on234 Schedulingof3-2and2-1 Eliminations, and a final image gathering mechanism based onData PaddingandMPI Rank Reorderingfor enabling the use ofMPI_Gathercollective operation. In addition, the hybrid MPI/OpenMP parallelism can also be applied to take advantage of current multi-node, multi-core architecture of modern HPC systems. We confirmed the scalability of the proposed approach by evaluating aBinary-Swapimplementation of234Compositoron theK computer, a Japanese leading-edge supercomputer installed at RIKEN AICS. We also evaluated an integration with HIVE (Heterogeneously Integrated Visual-analytic Environment) in order to verify a real-world usage. From the encouraging scalability results, we expect that this approach can also be useful even on the next-generation HPC systems which may demand higher level of parallelism.