ALICE Data Acquisition (DAQ)

ALICE Data Acquisition (DAQ)
Name	ALICE Data Acquisition (DAQ)
Location	CERN, Geneva
Detector	ALICE
Started	2008

ALICE Data Acquisition (DAQ) The ALICE Data Acquisition (DAQ) system is the primary event collection and transport infrastructure for the ALICE experiment at CERN. It coordinates readout from front-end electronics of subdetectors such as the Time Projection Chamber (TPC), Inner Tracking System (ITS), and Transition Radiation Detector (TRD) and delivers event data to the ALICE Offline processing and Worldwide LHC Computing Grid storage. DAQ integrates components developed by collaborations involving institutions like CERN, GSI Helmholtz Centre for Heavy Ion Research, Infn, and university groups from United Kingdom, Germany, and Italy.

Overview

The DAQ was designed to meet the data rates and complexity produced by heavy-ion collisions from the Large Hadron Collider at CERN, including runs during Run 1 (LHC), Run 2 (LHC), and upgrades for Run 3 (LHC). It interfaces with the Experiment Control System and the Trigger and Timing Control (TTC) systems while supporting online monitoring used by shifts organized by institutes such as Brookhaven National Laboratory and Lawrence Berkeley National Laboratory. DAQ is central to producing datasets used in analyses that probe phenomena like the Quark–Gluon Plasma and measurements first reported by ALICE collaboration papers.

Architecture and Components

The DAQ architecture is modular and layered, combining front-end electronics, readout drivers, event builders, and back-end storage. Key hardware blocks include readout units tied to subdetectors such as the Electromagnetic Calorimeter (EMCAL), Muon Spectrometer, and Photon Spectrometer (PHOS). Middleware and control layers implement software components analogous to systems used in experiments like ATLAS and CMS, while employing technologies shared with experiments at DESY and Fermilab. The design reflects contributions from projects funded by bodies such as the European Research Council, INFN, and national funding agencies.

Data Flow and Triggering

Data flow begins at the front-end electronics of detectors including the TPC, ITS, and TRD, traverses readout links to readout concentrators, and passes to event builders and storage elements. Trigger decisions are coordinated by the Central Trigger Processor interfacing to fast detectors like the V0 detector and the Zero Degree Calorimeter (ZDC). DAQ supports hardware-triggered data taking and, with upgrades, continuous readout modes similar to architectures used in future heavy-ion programs at RHIC and proposed at FAIR. The event-building stage aggregates fragments into complete events that are staged for transfer to the ALICE High-Level Trigger and the Grid.

Hardware and Networking

Hardware components include custom electronics such as readout boards, FPGA-based concentrators, and commercial servers from vendors often used by collaborations with CERN support. Networking is built on high-throughput switches, 10/40/100 Gigabit Ethernet fabrics, and Infiniband links comparable to deployments at Tier-0 centers and Tier-1 computing facilities. Storage arrays and tape libraries interface to the CERN Data Centre and the Worldwide LHC Computing Grid for long-term archival. Maintenance and procurement involve partners from laboratories like STFC and companies providing server and switch technologies.

Software and Middleware

DAQ software comprises readout control, run control, logging, and expert tools. It reuses and interoperates with frameworks and protocols used by experiments such as ALICE Offline frameworks, and components from ROOT and Gaudi where appropriate. Middleware includes data transport libraries, serialization formats, and monitoring GUIs used by shift crews from institutes like Nikhef and Czech Technical University. Configuration management, deployment, and testing employ tools and practices aligned with those at CERN IT and national computing centers.

Performance, Scalability, and Reliability

Performance targets are driven by collision rates and event sizes during Pb–Pb collisions and pp collisions. Scalability is achieved through horizontal scaling of event builders and buffering systems, drawing on lessons from experiments such as LHCb and CMS. Reliability measures include redundancy, automated failover, and monitoring integrated with the Detector Control System (DCS), enabling continuous operation across multi-week physics runs. Quantitative metrics tracked by operations teams include sustained throughput in GB/s, event acceptance, and deadtime fractions during physics and calibration runs.

Operational Experience and Upgrades

Operational experience from Run 1 (LHC) and Run 2 (LHC) informed upgrades for Run 3 (LHC), emphasizing higher bandwidth, continuous-readout capability, and tighter integration with the High-Level Trigger (HLT). Upgrade projects involved collaborations with institutes such as CERN groups, Universität Heidelberg, and University of Birmingham, and leveraged technologies from the European Grid Infrastructure and industry partners. Ongoing developments aim to support future physics programs, improve maintainability, and adapt to evolving networking and storage paradigms used across high-energy physics.

Category:ALICE experiment Category:CERN computing