ArcFVDSL, a DSEL Combined to HARTS, a Runtime System Layer to Implement Efficient Numerical Methods to Solve Diffusive Problems on New Heterogeneous Hardware Architecture
Nowadays, some frameworks like Arcane and Dune offer a number of advanced tools to deal with the complexity related to parallelism, meshes and linear solvers. However, they do not handle the high level complexity related to discretization methods and physical models. Generative programming and Domai...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2017-03-01
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| Series: | Oil & Gas Science and Technology |
| Online Access: | https://doi.org/10.2516/ogst/2017007 |
| Summary: | Nowadays, some frameworks like Arcane and Dune offer a number of advanced tools to deal with the complexity related to parallelism, meshes and linear solvers. However, they do not handle the high level complexity related to discretization methods and physical models. Generative programming and Domain Specific Languages (DSL) are key technologies allowing to write code with a high level expressive language and take advantage of the efficiency of generated code with low level services. DSL may be embedded in host languages like Python or C++. Such languages, named in that case Domain Specific Embedded Languages (DSEL), are applied for instance in frameworks like Fenics or Feel++ which are dedicated to the domain of Finite Element (FE) methods and Galerkin methods. ArcFVDSL is a DSEL developed on top of the Arcane framework, aiming to implement various lowest order methods (Finite-Volume (FV), Mimetic Finite Difference (MFD), Mixed Hybrid Finite Volume (MHFV), etc.) for diffusive problems on general meshes. In this paper, we present various implementations of different complex academic problems. We focus on the capability of the language to allow the description and the resolution of these problems with several lowest-order methods. We illustrate the benefits of such technology combined to runtime system tools like Heterogeneous Abstract RunTime System (HARTS) and its ability to handle seamlessly new heterogeneous architectures with multi-core processors enhanced by General Purpose computing on Graphics Processing Units (GP-GPU). We present the performance results of each implementation on different kinds of heterogeneous hardware architecture. |
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| ISSN: | 1294-4475 1953-8189 |