Parallel Computing for Module-Based Computational Experiment

Yao, Zhuo; Wang, Dali; Riccuito, Danial; Yuan, Fengming; Fang, Chunsheng

doi:10.1007/978-3-030-22741-8_27

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…• Yao, Wang, Riccuito, Yuan, and Fang (2019); Yao, Wang, Sun, and Zhong (2017) designed a UTF to generate unit tests. It is intended to make understanding undocumented source code easier and be suitable for large-scale software.…”

Section: Utfs In Computational Sciencementioning

confidence: 99%

Facilitating Test-Driven Development via Domain-Specific Languages in Computational Science Software Engineering

Gundlach,

Jung,

Hasselbring

2023

Preprint

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Research software plays a critical role in computational science. Therefore, the software should be of high quality. Producing such software involves efforts not only in initial development, but also during maintenance. One concept for improving the quality of software and reducing maintenance efforts is Test-Driven Development (TDD), which involves implementing tests, e.g., unit tests, as a specification for development. The effects are high test coverage and better overall software quality, but also additional effort in implementing tests. By separation of concerns, such additional efforts can be facilitated through the use of tailored notations such as domain-specific languages (DSLs). DSLs provide different levels of abstraction, for example, to separate the definition of tests from other concerns in software development. Not only does this incentivize research software engineers (RSEs) to write tests, but it also helps reduce the time required to write tests. The DSL TDD-DSL addresses this to facilitate the implementation of TDD using the Fortran Unit Testing Framework (UTF) pFUnit 4.0. TDD-DSL is focused on unit test definition and source code integration. It is implemented in Python for system under tests (SUTs) written in Fortran 90 or later. To reduce the effort of defining tests, TDD-DSL separates the test definition from the implementation and setup. Especially the latter can cause additional effort in practice, which can be mitigated by using code generators provided with the DSL tooling. The DSL allows describing test conditions as assertions and test cases as collections of assertions. TDD-DSL provides content assist within code editors for the underlying UTF, reducing the effort required in its deployment. It also supports parsing the SUT to expand the content assist with source code information and high-level error messaging for the test description. The content assist includes publicly available variables, types, functions and routines. TDD-DSL further supports the definition of unit values such as SI units to help Scientific Modelers check unit values in the software at runtime. For this purpose, the DSL tooling enables the generation of code templates for new implementations in the source code according to the defined tests. To simplify extending the DSL and improve overall maintainability, the DSL tooling employs the language server protocol (LSP) and also public available tools such as the ANTLR4 grammar. Using LSP also enables a multi-editor support to integrate the DSL tooling into different editors and IDEs. In this paper we report on the design and implementation of the DSL and its tooling as well as the evaluation with Scientific Modelers and RSEs.

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Section: Utfs In Computational Sciencementioning

confidence: 99%

Facilitating Test-Driven Development via Domain-Specific Languages in Computational Science Software Engineering

Gundlach,

Jung,

Hasselbring

2023

Preprint

View full text Add to dashboard Cite

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“…However, due to large memory and communication requirements, this platform is not computationally efficient to run over large combinations of sites and parameter values. Therefore, we developed a python-based version of the decomposition model, which is tested against the decomposition functional unit that uses the original ELM code for fidelity (Yao et al, 2019). The CTC and CNT versions of the functional unit submodel are referred to as CTCf and CNTf respectively.…”

Section: Functional Units and Simulation Proceduresmentioning

confidence: 99%

The impacts of model structure, parameter uncertainty and experimental design on Earth system model simulations of litter bag decomposition experiments

Ricciuto

Wang

Thornton

2021

Preprint

Self Cite

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Abstract. Accurate Earth system model simulations of the terrestrial carbon cycle and its feedbacks to climate critically depend on algorithms representing the decomposition of litter and soil organic matter. Litter bag studies, in which specific types of plant litter are subject to varying environmental conditions in the field and decomposition is measured, serve as valuable benchmarks for model performance. Here we test the Energy Exascale Earth System land model (ELM), which has two different structural representations of decomposition, using observations from the Long-term Intersite Decomposition Experiment (LIDET) over six different biomes and six different leaf litter types. We find that seasonal patterns in soil conditions and nutrient availability have large effects on decomposition rates, and that it is critical to include this in the simulation design. Despite widely differing base decomposition rates between the two different model structures, the models produce similar temporal patterns of decomposition when nitrogen is limiting. Both models overpredict the fraction of original nitrogen present as a function of carbon remaining when using default parameterizations. A parameter sensitivity analysis indicates strong dependence of model outputs on nitrogen limitation, carbon use efficiency and decomposition rates. A large spread in model predictions when considering an ensemble of possible parameter combinations strongly suggests parameter uncertainty may be more influential than model structural uncertainty, and that new measurement and modelling approaches may be necessary to constrain these uncertainties.

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Parallel Computing for Module-Based Computational Experiment

Cited by 2 publications

References 10 publications

Facilitating Test-Driven Development via Domain-Specific Languages in Computational Science Software Engineering

Facilitating Test-Driven Development via Domain-Specific Languages in Computational Science Software Engineering

The impacts of model structure, parameter uncertainty and experimental design on Earth system model simulations of litter bag decomposition experiments

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