Using ATLAS@Home to Exploit Extra CPU from Busy Grid Sites
Wenjing Wu, David Cameron, Di Qing · Computing and Software for Big Science · 2019
Grid computing typically provides most of the data processing resources for large high-energy physics experiments. However, typical grid sites are not fully utilized by regular workloads. To increase the CPU utilization of these grid sites, the ATLAS@Home volunteer computing framework can be used as a backfilling mechanism. Results show an extra 15–42% of CPU cycles can be exploited by backfilling grid sites running regular workloads, while the overall CPU utilization can remain over 0.9. Backfilling has no impact on the failure rate of the grid jobs, and the impact on the CPU efficiency of grid jobs varies from 0.02 to 0.11 depending on the configuration of the site. In addition, the throughput of backfill jobs in terms of CPU time per simulated event is the same as for resources dedicated to ATLAS@Home. This approach is sufficiently generic that it can easily be extended to other clusters.