Abstract
High-performance computing provides unprecedented capabilities to produce higher resolution 4-D models in a fraction of time. Thus, the need exists for a new generation of visualization systems able to maintain parity with the enormous volume of data generated. In attempting to write this much data to disk, each computational step introduces a significant performance bottleneck, yet most existing visualization software packages inherently rely on reading data in from a dump file. Available packages make this assumption of postprocessing at quite a fundamental level and are not very well suited for plotting very large numbers of specialized particles. This necessitates the creation of a new visualization system that meets the needs of large-scale geodynamic modeling. We have developed such a system, gLucifer, using a software framework approach that allows efficient reuse of our efforts in other areas of research. gLucifer is capable of producing movies of a 4-D data set “on the fly” (simultaneously with running the parallel scientific application) without creating a performance bottleneck. By eliminating most of the human efforts involved in visualizing results through postprocessing, gLucifer reconnects the scientist to the numerical experiment as it unfolds. Data sets that were previously very difficult to even manage may be efficiently explored and interrogated without writing to disk, and because this approach is based entirely on memory distributed across as many processors as are being utilized by the scientific application, the visualization solution is scalable into terabytes of data being rendered in real time.
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Acknowledgments
This work was carried out within one of the project funded by The Australian Computational Earth Systems Simulator (ACcESS). ACcESS is a major National Research Facility (MNRF) that emcompasses different institutes. The work described here has been developed from scientists from the Monash Cluster Computing (MCC) and software engineers from the Victorian Partnership for Advanced Computing (VPAC). We gratefully aknowledge Greg Watson who designed much of the original VTK modules, Cecile Duboz who lead the maintainance of the framework for nearly 2 years, as well as the Technical Support team at VPAC for installing libfame and Xvfb on several computer clusters, and the Monash Computer Science Summer Vacation Project for their support. We thank Cloudsea Wang and another reviewer for comments, which helped to improve this manuscript.
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Stegman, D.R., Moresi, L., Turnbull, R. et al. gLucifer: next generation visualization framework for high-performance computational geodynamics. Vis Geosci 13, 71–84 (2008). https://doi.org/10.1007/s10069-008-0010-2
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DOI: https://doi.org/10.1007/s10069-008-0010-2