Automated, Reliable, and Efficient Continental-Scale Replication of 7.3 Petabytes of Climate Simulation Data: A Case Study
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arXiv
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| Format: | Preprint |
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2024
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| author | Lacinski, Lukasz Liming, Lee Turoscy, Steven Harr, Cameron Chard, Kyle Dart, Eli Durack, Paul Ames, Sasha Hoffman, Forrest M. Foster, Ian T. |
| author_facet | Lacinski, Lukasz Liming, Lee Turoscy, Steven Harr, Cameron Chard, Kyle Dart, Eli Durack, Paul Ames, Sasha Hoffman, Forrest M. Foster, Ian T. |
| contents | We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) climate 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. This movement of some 29 million files, twice, undertaken in order to establish new ESGF nodes at ANL and ORNL, was performed largely automatically by a simple replication tool, a script that invoked Globus to transfer large bundles of files while tracking progress in a database. 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_19717 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automated, Reliable, and Efficient Continental-Scale Replication of 7.3 Petabytes of Climate Simulation Data: A Case Study Lacinski, Lukasz Liming, Lee Turoscy, Steven Harr, Cameron Chard, Kyle Dart, Eli Durack, Paul Ames, Sasha Hoffman, Forrest M. Foster, Ian T. Distributed, Parallel, and Cluster Computing We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) climate 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. This movement of some 29 million files, twice, undertaken in order to establish new ESGF nodes at ANL and ORNL, was performed largely automatically by a simple replication tool, a script that invoked Globus to transfer large bundles of files while tracking progress in a database. 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. |
| title | Automated, Reliable, and Efficient Continental-Scale Replication of 7.3 Petabytes of Climate Simulation Data: A Case Study |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2404.19717 |