sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 16-21, 2014

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Efficient I/O and Storage of Adaptive Resolution Data

SESSION: Big Data Analysis


TIME: 11:00AM - 11:30AM

SESSION CHAIR: Kelly Gaither

AUTHOR(S):Sidharth Kumar, John Edwards, Peer-Timo Bremer, Aaron Knoll, Cameron Christensen, Venkatram Vishwanath, Philip Carns, John A. Schmidt, Valerio Pascucci



We present an efficient, flexible, adaptive-resolution I/O framework that is suitable for both uniform and Adaptive Mesh Resolution (AMR) simulations. In an AMR setting, current solutions typically represent each resolution level as independent grids which often results in inefficient storage and performance. Our technique coalesces domain data into a unified, multi-resolution representation with fast spatially aggregated I/O. Furthermore, our framework easily extends to importance-driven storage of uniform grids, for example, by storing regions of interest at full resolution and nonessential regions at lower resolution for visualization or analysis. Our framework, which is an extension of the PIDX framework, achieves state of the art disk usage and I/O performance regardless of resolution of the data, regions of interest, and the number of processes that generated the data. We demonstrate the scalability and efficiency of our framework using the Uintah and S3D large-scale combustion codes on machines Mira and Edison.

Chair/Author Details:

Kelly Gaither (Chair) - Texas Advanced Computing Center

Sidharth Kumar - University of Utah

John Edwards - University of Utah

Peer-Timo Bremer - Lawrence Livermore National Laboratory

Aaron Knoll - University of Utah

Cameron Christensen - University of Utah

Venkatram Vishwanath - Argonne National Laboratory

Philip Carns - Argonne National Laboratory

John A. Schmidt - University of Utah

Valerio Pascucci - University of Utah

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Paper also available from IEEE Computer Society