Abstract

The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides around 100,000 cores, which are critical to ATLAS during data taking. When ATLAS is not recording data, such as the long shutdowns of the LHC, this large compute resource is used to generate and process simulation data for the experiment. At the beginning of the second long shutdown of the large hadron collider, the HLT farm including the Sim@P1 infrastructure was upgraded. Previous papers emphasised the need for simple, reliable, and efficient tools and assessed various options to quickly switch between data acquisition operation and offline processing. In this contribution, we describe the new mechanisms put in place for the opportunistic exploitation of the HLT farm for offline processing and give the results from the first months of operation.

Highlights

  • ATLAS [1] is a general purpose experiment located at point one (P1) of CERN’s Large Hadron Collider (LHC)

  • When working with Simulation at Point1 (Sim@P1) it is important to ensure the secure isolation from the physical resources at P1, seamless integration into the ATLAS distributed computing system, and reliable transition between the functions of the resources

  • We describe how the system was modified for operation with the upgraded High Level Trigger (HLT) hardware

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Summary

Introduction

ATLAS [1] is a general purpose experiment located at point one (P1) of CERN’s Large Hadron Collider (LHC). The virtual machines shared the “data” connection of the HLT hardware through a tagged virtual local area network (VLAN), which provided network isolation on the level of the Ethernet frame managed by the switches This VLAN allowed the virtual machines to connect to a controlled list of interfaces in the CERN general purpose network. When a rack is not needed for data taking a shifter can set that rack to offline operation This action triggers a change in the configuration database used by the TDAQ. The contextualisation sets up the computing environment for the ATLAS offline workloads and sets the virtual machines to advertise themselves to a HTCondor system running in the CERN general purpose network [9]. That means offline activities can potentially receive the full bandwidth available on the network, but will never impact traffic from other TDAQ activities — such as data taking

Content delivery
Persistent CVMFS caches
Operational experience
Returning the resources
Other workflows
Findings
Conclusions
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