Optimizing the HLT Buffer Strategy with Monte Carlo Simulations

This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.