Petalisp: run time code generation for operations on strided arrays

Heisig, Marco; Köstler, Harald

doi:10.1145/3219753.3219755

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Code Generation For Geometric Multigrid Solvers1

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2020

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“…Therefore, in the last years, various approaches to automate the process to derive a simulation code from a mathematical model by code generation have been explored. Our group conducted research in several projects on both external and embedded domain-specific HPC languages in Python [5], Scala [30], AnyDSL [52], C++ and CommonLisp [26].…”

Section: Code Generation For Geometric Multigrid Solversmentioning

confidence: 99%

Code generation approaches for parallel geometric multigrid solvers

Köstler¹,

Heisig²,

Kohl³

et al. 2020

Analele Universitatii "Ovidius" Constanta - Seria Matematica

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Software development for applications in computational science and engineering has become complex in recent years. This is mainly due to the increasing parallelism and heterogeneity in modern computer architectures and to the more realistic physical and mathematical models that have to be processed. One idea to address this issue is to use code generation techniques. In contrast to manual implementations in a general-purpose computing language, they allow to integrate automatic code transforms to produce efficient code for different models and platforms. As an example the numerical solution of an elliptic partial differential equation via generated geometric multigrid solvers is considered. We present three code generation approaches for it and discuss their advantages and disadvantages with respect to performance, portability, and productivity.

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Section: Code Generation For Geometric Multigrid Solversmentioning

confidence: 99%