کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6922268 1448274 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection
ترجمه فارسی عنوان
درون گرایی ممکن است بیشتر به دست آورد: افزایش مدل های موجود ژئوسنیکال با انعکاس ساختاری شبیه سازی زبان مادری
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Geoscientific models manage myriad and increasingly complex data structures as trans-disciplinary models are integrated. They often incur significant redundancy with cross-cutting tasks. Reflection, the ability of a program to inspect and modify its structure and behavior at runtime, is known as a powerful tool to improve code reusability, abstraction, and separation of concerns. Reflection is rarely adopted in high-performance Geoscientific models, especially with Fortran, where it was previously deemed implausible. Practical constraints of language and legacy often limit us to feather-weight, native-language solutions. We demonstrate the usefulness of a structural-reflection-emulating, dynamically-linked metaObjects, gd. We show real-world examples including data structure self-assembly, effortless input/output (IO) and upgrade to parallel I/O, recursive actions and batch operations. We share gd and a derived module that reproduces MATLAB-like structure in Fortran and C++. We suggest that both a gd representation and a Fortran-native representation are maintained to access the data, each for separate purposes. Embracing emulated reflection allows generically-written codes that are highly re-usable across projects.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 110, January 2018, Pages 32-40
نویسندگان
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