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Data · dataset · 2026

KGEN: A Python tool for automated Fortran kernel generation and verification

Listed in National Center for Atmospheric Research

Computational kernels, which are small pieces of software that selectively capture the characteristics of larger applications, have been used successfully for decades.

Description

Kernels allow for the testing of a compiler's ability to optimize code, performance of future hardware and reproducing compiler bugs. Unfortunately they can be rather time consuming to create and do not always accurately represent the full complexity of large scientific applications.

Furthermore, expert knowledge is often required to create such kernels. In this paper, we present a Python-based tool that greatly simplifies the generation of computational kernels from Fortran based applications. Our tool automatically extracts partial source code of a larger Fortran application into a stand-alone executable kernel.

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Additionally, our tool also generates state data necessary for proper execution and verification of the extracted kernel. We have utilized our tool to extract more than thirty computational kernels from a million-line climate simulation model. Our extracted kernels have been used for a variety of purposes including: code modernization, identification of limitations in compiler optimizations, numerical algorithm debugging, compiler bug reporting, and for procurement benchmarking.

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Inferred from text
Climate model simulation 65% · Simulation 75%
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Research94ac28c1-39b0-438a-8b54-4771397806f611 d agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[method].local:method:climate-modelenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (65%)
concepts[method].local:method:simulationenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0