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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2203.00925 |
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| _version_ | 1866916513463664640 |
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| author | Kissami, Imad Ratnani, Ahmed |
| author_facet | Kissami, Imad Ratnani, Ahmed |
| contents | Manapy is a parallel, unstructured, finite-volume based solver for the solution of partial differential equations (PDE). The framework is written using Python, it is object-oriented, and is organized in such a way that it is easy to understand and modify. In this paper, we present the parallel implementation and scalability of the differential operators used on a general case of PDE. The performance of massively parallel direct and iterative methods for solving large sparse systems of linear equations in plasma physics is evaluated on a latest high performance computing system, and 3D test cases for plasma physics are presented. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_00925 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Manapy: MPI-Based framework for solving partial differential equations using finite-volume on unstructured-grid Kissami, Imad Ratnani, Ahmed Distributed, Parallel, and Cluster Computing Manapy is a parallel, unstructured, finite-volume based solver for the solution of partial differential equations (PDE). The framework is written using Python, it is object-oriented, and is organized in such a way that it is easy to understand and modify. In this paper, we present the parallel implementation and scalability of the differential operators used on a general case of PDE. The performance of massively parallel direct and iterative methods for solving large sparse systems of linear equations in plasma physics is evaluated on a latest high performance computing system, and 3D test cases for plasma physics are presented. |
| title | Manapy: MPI-Based framework for solving partial differential equations using finite-volume on unstructured-grid |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2203.00925 |