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ASAGI: A Parallel Server for Adaptive Geoinformation
| Content Provider | ACM Digital Library |
|---|---|
| Author | Gabriel, Alice-Agnes Rettenberger, Sebastian Meister, Oliver Bader, Michael |
| Abstract | We present ASAGI, an open-source library with a simple interface to access Cartesian material and geographic datasets in massively parallel simulations with dynamically adaptive mesh refinement (AMR). ASAGI distributes geographic datasets over all compute nodes storing only a portion of the dataset on each node. An automatic replication mechanism copies the data between nodes to assure fast local access even after load migration in the application. We demonstrate ASAGI's preparedness for up-to-petascale simulations in three use cases. We simulate a Tsunami on 512 cores and a porous media flow on up to 8,192 cores of SuperMUC with the AMR framework sam(oa)2. We also run an earthquake simulation with SeiSol on 65,536 cores. For all applications, ASAGI provides large complex 3D material datasets required for the realistic scenarios. The NUMA-awareness of ASAGI turned out to be especially useful for the hybrid MPI+OpenMP parallelization of both codes. |
| Starting Page | 1 |
| Ending Page | 9 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781450341226 |
| DOI | 10.1145/2938615.2938618 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-04-26 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Large scale applications Adaptive mesh refinement Geoinformation Realistic simulations |
| Content Type | Text |
| Resource Type | Article |
