SC13 Home > SC13 Schedule > SC13 Presentation - Assessing the Effects of Data Compression in Simulations Using Physically Motivated Metrics

SCHEDULE: NOV 16-22, 2013

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Assessing the Effects of Data Compression in Simulations Using Physically Motivated Metrics

SESSION: In-Situ Data Analytics and Reduction

EVENT TYPE: Papers, Awards, Best Paper Finalists

TIME: 1:30PM - 2:00PM

SESSION CHAIR: Dimitris Nikolopoulos

AUTHOR(S):Daniel E. Laney, Steven H. Langer, Christopher R. Weber, Peter G. Lindstrom, Al Wegener


This paper examines whether lossy compression can be used effectively in physics simulations as a possible strategy to combat the expected data-movement bottleneck in future high performance computing architectures. We show that, for the codes and simulations we tested, compression levels of 3--5X can be applied without causing significant changes to important physical quantities. Rather than applying signal processing error metrics, we utilize physics-based metrics appropriate for each code to assess the impact of compression. We evaluate three different simulation codes: a Lagrangian shock-hydrodynamics code, an Eulerian higher-order hydrodynamics turbulence modeling code, and an Eulerian coupled laser-plasma interaction code. We compress relevant quantities after each time-step to approximate the effects of tightly coupled compression and study the compression rates to estimate memory and disk-bandwidth reduction. We find that the error characteristics of compression algorithms must be carefully considered in the context of the underlying physics being modeled.

Chair/Author Details:

Dimitris Nikolopoulos (Chair) - Queen's University Belfast

Daniel E. Laney - Lawrence Livermore National Laboratory

Steven H. Langer - Lawrence Livermore National Laboratory

Christopher R. Weber - Lawrence Livermore National Laboratory

Peter G. Lindstrom - Lawrence Livermore National Laboratory

Al Wegener - Samplify Systems

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The full paper can be found in the ACM Digital Library