Abstract

The LHCb experiment at the LHC accelerator at CERN collects collisions of particle bunches at 40 MHz. After a first level of hardware trigger with output of 1 MHz, the physically interesting collisions are selected by running dedicated trigger algorithms in the High Level Trigger (HLT) computing farm. This farm consists of up to roughly 25000 CPU cores in roughly 1600 physical nodes each equipped with at least 1 TB of local storage space. This work describes the architecture to treble the available CPU power of the HLT farm given that the LHC collider in previous years delivered stable physics beams about 30% of the time. The gain is achieved by splitting the event selection process in two, a first stage reducing the data taken during stable beams and buffering the preselected particle collisions locally. A second processing stage running constantly at lower priority will then finalize the event filtering process and benefits fully from the time when LHC does not deliver stable beams e.g. while preparing a new physics fill or during periods used for machine development.

Highlights

  • – Not the physics details of this split : Introduction of basic concepts used in the realization

  • – Loose coupling through local disk cache – HLT1 must execute real-time – HLT2 executes with lower priority

  • – Large benefit from copy-on-write (~70% of memory) Trigger processes forked after configuration phase

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Summary

Introduction

– Not the physics details of this split : Introduction of basic concepts used in the realization. The use of periods without beam for online high level triggers ● HLT (expected for 2015): ~ 1600 Nodes ~ 25000 CPU cores ~ 45000 Trigger processes ~ 5000 Infrastructure tasks Monitoring Cluster Low level monitoring using raw data Reconstruction Cluster High level monitoring with fully reconstructed events ● LHC delivers roughly during 30% of the running period stable beams to LHCb

Results
Conclusion
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