SCHEDULE: NOV 10-16, 2012
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Efficient Data Restructuring and Aggregation for IO Acceleration in PIDX
SESSION: Optimizing I/O For Analytics
EVENT TYPE: Papers
TIME: 11:30AM - 12:00PM
SESSION CHAIR: Dean Hildebrand
AUTHOR(S):Sidharth Kumar, Venkatram Vishwanath, Philip Carns, Joshua A. Levine, Robert Latham, Giorgio Scorzelli, Hemanth Kolla, Ray Grout, Jacqueline Chen, Robert Ross, Michael E. Papka, Valerio Pascucci
ROOM:355-D
ABSTRACT:
Hierarchical, multi-resolution data representations enable interactive analysis and visualization of large-scale simulations. One promising application of these techniques is to store HPC simulation output in a hierarchical Z (HZ) ordering that translates data from a Cartesian coordinate scheme to a one dimensional
array ordered by locality at different resolution levels. However, when the dimensions of the simulation data are not an even power of two, parallel HZ-ordering produces sparse memory and network access patterns that inhibit I/O
performance. This work presents a new technique for parallel HZ-ordering of simulation datasets that restructures simulation data into large power of two blocks to facilitate efficient I/O aggregation. We perform both weak and strong scaling experiments using the S3D combustion application on both Cray-XE6 (65536 cores) and IBM BlueGene/P (131072 cores) platforms. We demonstrate that data can be written in hierarchical, multiresolution format with performance competitive to that of native data ordering methods.
Chair/Author Details:
Dean Hildebrand (Chair) - IBM Almaden Research Center
Sidharth Kumar - University of Utah
Venkatram Vishwanath - Argonne National Laboratory
Philip Carns - Argonne National Laboratory
Joshua A. Levine - University of Utah
Robert Latham - Argonne National Laboratory
Giorgio Scorzelli - University of Utah
Hemanth Kolla - Sandia National Laboratories
Ray Grout - National Renewable Energy Laboratory
Jacqueline Chen - Sandia National Laboratories
Robert Ross - Argonne National Laboratory
Michael E. Papka - Argonne National Laboratory
Valerio Pascucci - University of Utah
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Efficient Data Restructuring and Aggregation for IO Acceleration in PIDX
SESSION: Optimizing I/O For Analytics
EVENT TYPE:
TIME: 11:30AM - 12:00PM
SESSION CHAIR: Dean Hildebrand
AUTHOR(S):Sidharth Kumar, Venkatram Vishwanath, Philip Carns, Joshua A. Levine, Robert Latham, Giorgio Scorzelli, Hemanth Kolla, Ray Grout, Jacqueline Chen, Robert Ross, Michael E. Papka, Valerio Pascucci
ROOM:355-D
ABSTRACT:
Hierarchical, multi-resolution data representations enable interactive analysis and visualization of large-scale simulations. One promising application of these techniques is to store HPC simulation output in a hierarchical Z (HZ) ordering that translates data from a Cartesian coordinate scheme to a one dimensional
array ordered by locality at different resolution levels. However, when the dimensions of the simulation data are not an even power of two, parallel HZ-ordering produces sparse memory and network access patterns that inhibit I/O
performance. This work presents a new technique for parallel HZ-ordering of simulation datasets that restructures simulation data into large power of two blocks to facilitate efficient I/O aggregation. We perform both weak and strong scaling experiments using the S3D combustion application on both Cray-XE6 (65536 cores) and IBM BlueGene/P (131072 cores) platforms. We demonstrate that data can be written in hierarchical, multiresolution format with performance competitive to that of native data ordering methods.
Chair/Author Details:
Dean Hildebrand (Chair) - IBM Almaden Research Center
Sidharth Kumar - University of Utah
Venkatram Vishwanath - Argonne National Laboratory
Philip Carns - Argonne National Laboratory
Joshua A. Levine - University of Utah
Robert Latham - Argonne National Laboratory
Giorgio Scorzelli - University of Utah
Hemanth Kolla - Sandia National Laboratories
Ray Grout - National Renewable Energy Laboratory
Jacqueline Chen - Sandia National Laboratories
Robert Ross - Argonne National Laboratory
Michael E. Papka - Argonne National Laboratory
Valerio Pascucci - University of Utah
Click here to download .ics calendar file