Speaker
Description
With increasing data volume from Nuclear Physics experiments requirements to data
storage and access are changing. To keep up with large data sets new data formats
are needed for efficient processing and analysis of the data. Frequently, in the
experiments data goes through stages from data acquisition to reconstruction and
data analysis and data is converted from one format to another causing waisted CPU
cycles.
In this work we present High Performance Output (HIPO) data format developed
for CLAS12 experiment at Jefferson National Laboratory. It was designed to fit the needs
of data acquisition and high level data analysis, to avoid data format conversions
at different stages of data processing. The new format was designed
to store different event topologies from reconstructed data in tagged form
for efficient access by different analysis groups. In centralized data skimming
applications HIPO data format significantly outperforms standard data formats
used in Nuclear and High Energy Physics (ROOT) and industry standard formats,
such as Apache Avro and Apache Parquet.
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