GPU accelerated particle visualisation with Splotch

M. Rivi, C. Gheller, Tim Dykes, Mel Krokos, K. Dolag

Research output: Contribution to journalArticlepeer-review

68 Downloads (Pure)

Abstract

Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.
Original languageEnglish
Pages (from-to)9-18
JournalAstronomy and Computing
Volume5
Early online date22 Mar 2014
DOIs
Publication statusPublished - Jul 2014

Keywords

  • scientific visualization
  • astrophysics
  • CUDA
  • high-performance computing

Fingerprint

Dive into the research topics of 'GPU accelerated particle visualisation with Splotch'. Together they form a unique fingerprint.

Cite this