A Hybrid In Situ Approach for Cost Efficient Image Database Generation

Valentin Bruder*, Matthew Larsen, Thomas Ertl, Hank Childs, Steffen Frey

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
19 Downloads (Pure)


The visualization of results while the simulation is running is increasingly common in extreme scale computing environments. We present a novel approach for in situ generation of image databases to achieve cost savings on supercomputers. Our approach, a hybrid between traditional inline and in transit techniques, dynamically distributes visualization tasks between simulation nodes and visualization nodes, using probing as a basis to estimate rendering cost. Our hybrid design differs from previous works in that it creates opportunities to minimize idle time from four fundamental types of inefficiency: variability, limited scalability, overhead, and rightsizing. We demonstrate our results by comparing our method against both inline and in transit methods for a variety of configurations, including two simulation codes and a scaling study that goes above 19K cores. Our findings show that our approach is superior in many configurations. As in situ visualization becomes increasingly ubiquitous, we believe our technique could lead to significant amounts of reclaimed cycles on supercomputers.

Original languageEnglish
Pages (from-to)3788 - 3798
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number9
Early online date29-Apr-2022
Publication statusPublished - 1-Sept-2023


  • Computational modeling
  • Costs
  • Data models
  • Data visualization
  • High performance computing
  • In situ
  • Scalability
  • Supercomputers
  • Task analysis
  • Visualization

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