High-performance astrophysical visualization using Splotch

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

Research output: Contribution to journalArticlepeer-review


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
Issue number1
Publication statusPublished - 31 May 2010


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


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