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
ROOM:205/207
ABSTRACT:
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