Fast JSON parser using metaprogramming on GPU

We demonstrate a new idea of a parallel GPU JSON parser, which is able to optimize the parsing and initial transformation process through metaprogramming. It outperforms other well-known solutions like simdjson, Pandas, as well as cuDF- which also works on GPU. The resulting data is ready to be furt...

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Bibliographic Details
Published in2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) pp. 1 - 10
Main Authors Kaczmarski, Krzysztof, Narebski, Jakub, Piotrowski, Stanislaw, Przymus, Piotr
Format Conference Proceeding
LanguageEnglish
Published IEEE 13.10.2022
Subjects
Data science
ETL
GPU
Graphics processing units
JSON
metaprogramming
parallel parser
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Summary:We demonstrate a new idea of a parallel GPU JSON parser, which is able to optimize the parsing and initial transformation process through metaprogramming. It outperforms other well-known solutions like simdjson, Pandas, as well as cuDF- which also works on GPU. The resulting data is ready to be further processed in common data frame formats and may be incorporated by RAPIDS, Apache Arrow or Pandas. Our parser can therefore be a part of an industrial Extract-Transform-Load workflow.
DOI:10.1109/DSAA54385.2022.10032381