Automated, reliable, and efficient continental-scale replication of 7.3 petabytes of computational simulation data: A case study

We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) computational simulation data from Lawrence Livermore National Laboratory (LLNL) in California to Argonne National Laboratory (ANL) in Illinois and Oak Ridge National Laboratory (ORNL) in Tennessee—a task motivated by a need for increased reliability, capacity, and performance. This task presented significant challenges: the need to move 29 million files twice under time pressure from aging storage hardware; a source file system bottleneck limiting throughput to 1.5 GB/s; frequent site maintenance windows; and the need for complete reliability at scale. We addressed these challenges using a simple replication tool that invoked Globus to transfer large bundles of files while tracking progress in a database, dynamically rerouting transfers to work around maintenance periods and file system limitations. Under the covers, Globus organized transfers to make efficient use of the high-speed Energy Sciences network (ESnet) and the data transfer nodes deployed at participating sites, and also addressed security, integrity checking, and recovery from a variety of transient failures. This success demonstrates the considerable benefits that can accrue from the adoption of performant data replication infrastructure. The replication tool is available at https://github.com/esgf2-us/data-replication-tools .

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Publication Details

Journal
The International Journal of High Performance Computing Applications
Published
2026-04-25
DOI
https://doi.org/10.1177/10943420261441742
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Automated, reliable, and efficient continental-scale replication of 7.3 petabytes of computational simulation data: A case study

Cameron Harr, Ian Foster, Sasha Ames, Forrest M. Hoffman et al.
The International Journal of High Performance Computing Applications
Distributed and Parallel Computing Systems
article

Automated, reliable, and efficient continental-scale replication of 7.3 petabytes of computational simulation data: A case study

Cameron Harr, Ian Foster, Sasha Ames, Forrest M. Hoffman, Kyle Chard, Łukasz Łaciński, Lee Liming, Steven Turoscy, Paul J. Durack, Eli Dart
article en

Abstract

We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) computational simulation data from Lawrence Livermore National Laboratory (LLNL) in California to Argonne National Laboratory (ANL) in Illinois and Oak Ridge National Laboratory (ORNL) in Tennessee—a task motivated by a need for increased reliability, capacity, and performance. This task presented significant challenges: the need to move 29 million files twice under time pressure from aging storage hardware; a source file system bottleneck limiting throughput to 1.5 GB/s; frequent site maintenance windows; and the need for complete reliability at scale. We addressed these challenges using a simple replication tool that invoked Globus to transfer large bundles of files while tracking progress in a database, dynamically rerouting transfers to work around maintenance periods and file system limitations. Under the covers, Globus organized transfers to make efficient use of the high-speed Energy Sciences network (ESnet) and the data transfer nodes deployed at participating sites, and also addressed security, integrity checking, and recovery from a variety of transient failures. This success demonstrates the considerable benefits that can accrue from the adoption of performant data replication infrastructure. The replication tool is available at https://github.com/esgf2-us/data-replication-tools .

The International Journal of High Performance Computing ApplicationsVol. 40(3)
Argonne National Laboratory (US), Lawrence Livermore National Laboratory (US), Oak Ridge National Laboratory (US), Lawrence Berkeley National Laboratory (US), University of Chicago (US)
Biological and Environmental Research
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Distributed and Parallel Computing Systems
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