Diving deep: Data-management and visualization strategies for adaptive mesh refinement simulations

Michael L. Norman; John Shalf; Stuart Levy; Gregory Daues

doi:10.1109/5992.774839

Diving deep: Data-management and visualization strategies for adaptive mesh refinement simulations

Michael L. Norman, John Shalf, Stuart Levy, Gregory Daues

National Center for Supercomputing Applications (NCSA)

Research output: Contribution to journal › Article › peer-review

Abstract

The authors' cosmological applications illustrate problems and solutions in storing, handling, visualizing, virtually navigating, and remote-serving data produced by large-scale adaptive mesh refinement simulations.

Original language	English (US)
Pages (from-to)	36-46
Number of pages	11
Journal	Computing in Science and Engineering
Volume	1
Issue number	4
DOIs	https://doi.org/10.1109/5992.774839
State	Published - 1999

ASJC Scopus subject areas

General Computer Science
General Engineering

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10.1109/5992.774839

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title = "Diving deep: Data-management and visualization strategies for adaptive mesh refinement simulations",

abstract = "The authors' cosmological applications illustrate problems and solutions in storing, handling, visualizing, virtually navigating, and remote-serving data produced by large-scale adaptive mesh refinement simulations.",

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Diving deep: Data-management and visualization strategies for adaptive mesh refinement simulations

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