ETH: A Framework for the Design-Space Exploration of Extreme-Scale Visualization
| dc.contributor.author | Abrams, Gregory | en |
| dc.contributor.author | Adhinarayanan, Vignesh | en |
| dc.contributor.author | Feng, Wu-chun | en |
| dc.contributor.author | Rogers, David | en |
| dc.contributor.author | Ahrens, Jams | en |
| dc.contributor.author | Wilson, Luke | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2017-09-29T18:15:22Z | en |
| dc.date.available | 2017-09-29T18:15:22Z | en |
| dc.date.issued | 2017-09-29 | en |
| dc.description.abstract | As high-performance computing (HPC) moves towards the exascale era, large-scale scientific simulations are generating enormous datasets. A variety of techniques (e.g., in-situ methods, data sampling, and compression) have been proposed to help visualize these large datasets under various constraints such as storage, power, and energy. However, evaluating these techniques and understanding the various trade-offs (e.g., performance, efficiency, quality) remains a challenging task. To enable the investigation and optimization across such tradeoffs, we propose a toolkit for the early-stage exploration of visualization and rendering approaches, job layout, and visualization pipelines. Our framework covers a broader parameter space than existing visualization applications such as ParaView and VisIt. It also promotes the study of simulation-visualization coupling strategies through a data-centric approach, rather than requiring the code itself. Furthermore, with experimentation on an extensively instrumented supercomputer, we study more metrics of interest than was previously possible. Overall, our framework will help to answer important what-if scenarios and trade-off questions in early stages of pipeline development, helping scientists to make informed choices about how to best couple a simulation code with visualization at extreme scale. | en |
| dc.description.sponsorship | This material is based upon work supported by Dr. Lucy Nowell of the U.S. Department of Energy Office of Science, Advanced Scientific Computing Research under Award Numbers DE-SC0012513, DE-SC0012637, and DE-SC-0012516. We would like to acknowledge Galen Gisler (LANL) for the asteroid simulation and contributors to the hardware/hybrid accelerated cosmology Code (HACC). This work was published under LANL release LA-UR-17-26715. | en |
| dc.identifier.trnumber | TR-17-05 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/79454 | en |
| dc.language.iso | en | en |
| dc.publisher | Department of Computer Science, Virginia Polytechnic Institute & State University | en |
| dc.relation.ispartof | Computer Science Technical Reports | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | High Performance Computing | en |
| dc.subject | Parallel and Distributed Computing | en |
| dc.subject | Computer Systems | en |
| dc.subject | Algorithms | en |
| dc.subject | Computational Science and Engineering | en |
| dc.subject | Modeling and Simulation | en |
| dc.title | ETH: A Framework for the Design-Space Exploration of Extreme-Scale Visualization | en |
| dc.type | Technical report | en |
| dc.type.dcmitype | Text | en |