The CERN ATLAS experiment grid workflow system manages routinely 250 to
500 thousand concurrently running production and analysis jobs
to process simulation and detector data. In total more than 300 PB
of data is distributed over more than 150 sites in the WLCG.
At this scale small improvements in the software and computing
performance and workflows can lead to significant resource usage gains.
ATLAS is reviewing together with CERN IT experts several typical
simulation and data processing workloads for potential performance
improvements in terms of memory and CPU usage, disk and network I/O.
All ATLAS production and analysis grid jobs are instrumented to collect
many performance metrics for detailed statistical studies using
modern data analytics tools like ElasticSearch and Kibana.
This presentation will review and explain the performance gains of
several ATLAS simulation and data processing workflows and present
analytics studies of the ATLAS grid workflows.