Conveners
Parallel (Track 2): Online and real-time computing
- Christina Agapopoulou (Université Paris-Saclay (FR))
Parallel (Track 2): Online and real-time computing
- David Rohr (CERN)
Parallel (Track 2): Online and real-time computing
- Kunihiro Nagano (KEK High Energy Accelerator Research Organization (JP))
Parallel (Track 2): Online and real-time computing
- David Rohr (CERN)
Parallel (Track 2): Online and real-time computing
- Kunihiro Nagano (KEK High Energy Accelerator Research Organization (JP))
Parallel (Track 2): Online and real-time computing
- Christina Agapopoulou (Université Paris-Saclay (FR))
Parallel (Track 2): Online and real-time computing
- Christina Agapopoulou (Université Paris-Saclay (FR))
Parallel (Track 2): Online and real-time computing
- David Rohr (CERN)
Description
Online and real-time computing
Since 2022, the LHCb detector is taking data with a full software trigger at the LHC proton-proton collision rate, implemented in GPUs in the first stage and CPUs in the second stage. This setup allows to perform the alignment & calibration online and to perform physics analyses directly on the output of the online reconstruction, following the real-time analysis paradigm. This talk will give...
The ATLAS experiment in the LHC Run 3 uses a two-level trigger system to select
events of interest to reduce the 40 MHz bunch crossing rate to a recorded rate
of up to 3 kHz of fully-built physics events. The trigger system is composed of
a hardware based Level-1 trigger and a software based High Level Trigger.
The selection of events by the High Level Trigger is based on a wide variety...
Timepix4 is an innovative multi-purpose ASIC developed by the Medipix4 Collaboration at CERN for fundamental and applied physics detection systems. It is composed by a ~7cm$^2$ area matrix with about 230k independent pixels, each one with a charge integration circuit, a discriminator and a time-to-digital converter that allows to measure Time-of-Arrival with 195 ps width bins and...
The NA62 experiment is designed to study kaon’s rare decays using a decay-in-flight technique. Its Trigger and Data Acquisition (TDAQ) system is multi-level, making it critically dependent on the performance of the inter-level network.
To manage the enormous amount of data produced by the detectors, three levels of triggers are used. The first level L0TP, implemented using an FPGA device, has...
Digital ELI-NP List-mode Acquisition (DELILA) is a data acquisition (DAQ) system for the Variable Energy GAmma (VEGA) beamline system at Extreme Light Infrastructure – Nuclear Physics (ELI-NP), Magurele, Romania [1]. ELI-NP has been implementing the VEGA beamline and entirely operate the beamline in 2026. Several different detectors/experiments (e.g. High Purity Ge (HPGe) detectors, Si...
The ePIC collaboration adopted the JANA2 framework to manage its reconstruction algorithms. This framework has since evolved substantially in response to ePIC's needs. There have been three main design drivers: integrating cleanly with the PODIO-based data models and other layers of the key4hep stack, enabling external configuration of existing components, and supporting timeframe splitting...
The CBM experiment, currently being constructed at GSI/FAIR, aims to investigate QCD at high baryon densities. The CBM First-level Event Selector (FLES) serves as the central event selection system of the experiment. It functions as a high-performance computer cluster tasked with the online analysis of physics data, including full event reconstruction, at an incoming data rate which exceeds 1...
The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start
operating in 2029, aims to increase the instantaneous luminosity by a factor of
10 compared to the LHC. To match this increase, the ATLAS experiment has been
implementing a major upgrade program divided into two phases. The first phase
(Phase-I), completed in 2022, introduced new trigger and detector systems that
have...
The data acquisition (DAQ) system stands as an essential component within the CMS experiment at CERN. It relies on a large network system of computers with demanding requirements on control, monitoring, configuration and high throughput communication. Furthermore, the DAQ system must accommodate various application scenarios, such as interfacing with external systems, accessing custom...
The CBM First-level Event Selector (FLES) serves as the central data processing and event selection system for the upcoming CBM experiment at FAIR. Designed as a scalable high-performance computing cluster, it facilitates online analysis of unfiltered physics data at rates surpassing 1 TByte/s.
As the input to the FLES, the CBM detector subsystems deliver free-streaming, self-triggered data...
The ATLAS experiment at the Large Hadron Collider (LHC) at CERN continuously
evolves its Trigger and Data Acquisition (TDAQ) system to meet the challenges
of new physics goals and technological advancements. As ATLAS prepares for the
Phase-II Run 4 of the LHC, significant enhancements in the TDAQ Controls and
Configuration tools have been designed to ensure efficient data...
The DarkSide-20k detector is now under construction in the Gran Sasso National Laboratory (LNGS) in Italy, the biggest underground physics facility. It is designed to directly detect dark matter by observing weakly interacting massive particles (WIMPs) scattering off the nuclei in 20 tonnes of underground-sourced liquid argon in the dual-phase time projection chamber (TPC). Additionally two...
Ensuring the quality of data in large HEP experiments such as CMS at the LHC is crucial for producing reliable physics outcomes. The CMS protocols for Data Quality Monitoring (DQM) are based on the analysis of a standardized set of histograms offering a condensed snapshot of the detector's condition. Besides the required personpower, the method has a limited time granularity, potentially...
Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7...
The first level of the trigger system of the LHCb experiment (HLT1) reconstructs and selects events in real-time at the LHC bunch crossing rate in software using GPUs. It must carefully balance a broad physics programme that extends from kaon physics up to the electroweak scale. An automated procedure to determine selection criteria is adopted that maximises the physics output of the entirety...
The architecture of the existing ALICE Run 3 on-line real time visualization solution was designed for easy modification of the visualization method used. In addition to the existing visualization based on the desktop application, a version using browser-based visualization has been prepared. In this case, the visualization is computed and displayed on the user's computer. There is no need to...
The LHCb experiment at CERN has undergone a comprehensive upgrade. In particular, its trigger system has been completely redesigned into a hybrid-architecture, software-only system that delivers ten times more interesting signals per unit time than its predecessor. This increased efficiency - as well as the growing diversity of signals physicists want to analyse - makes conforming to crucial...
A new algorithm, called "Downstream", has been developed and implemented at LHCb, which is able to reconstruct and select very displaced vertices in real time at the first level of the trigger (HLT1). It makes use of the Upstream Tracker (UT) and the Scintillator Fiber detector (SciFI) of LHCb and it is executed on GPUs inside the Allen framework. In addition to an optimized strategy, it...
The event reconstruction in the CBM experiment is challenging.
There will be no simple hardware trigger due to the novel concepts of free-streaming data and self-triggered front-end electronics.
Thus, there is no a priori association of signals to physical events.
CBM will operate at interaction rates of 10 MHz, unprecedented for heavy ion experiments.
At this rate, collisions overlap...
In this presentation, we introduce BuSca, a prototype algorithm designed for real-time particle searches, leveraging the enhanced parallelization capabilities of the new LHCb trigger scheme implemented on GPUs. BuSca is focused on downstream reconstructed tracks, detected exclusively by the UT and SciFi detectors. By projecting physics candidates onto 2D histograms of flight distance and mass...
Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics (HEP) experiments. A necessary component of reconstruction algorithms is particle identification (PID) that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics...
Ahead of Run 3 of the LHC, the trigger of the LHCb experiment was redesigned. The L0 hardware stage present in Runs 1 and 2 was removed, with detector readout at 30 MHz passing directly into the first stage of the software-based High Level Trigger (HLT), run on GPUs. Additionally, the second stage of the upgraded HLT makes extensive use of the Turbo event model, wherein only those candidates...
The evergrowing amounts of data produced by the high energy physics experiments create a need for fast and efficient track reconstruction algorithms. When storing all incoming information is not feasible, online algorithms need to provide reconstruction quality similar to their offline counterparts. To achieve it, novel techniques need to be introduced, utilizing acceleration offered by the...
The Mu3e experiment at the Paul-Scherrer-Institute will be searching for the charged lepton flavor violating decay $\mu^+ \rightarrow e^+e^-e^+$. To reach its ultimate sensitivity to branching ratios in the order of $10^{-16}$, an excellent momentum resolution for the reconstructed electrons is required, which in turn necessitates precise detector alignment. To compensate for weak modes in the...
The increasing complexity and data volume of Nuclear Physics experiments require significant computing resources to process data from experimental setups. The entire experimental data set has to be processed to extract sub-samples for physics analysis. The advancements in Artificial Intelligence and Machine Learning fields provide tools and procedures that can significantly enhance the...
The reconstruction of charged particle trajectories in tracking detectors is crucial for analyzing experimental data in high-energy and nuclear physics. Processing of the vast amount of data generated by modern experiments requires computationally efficient solutions to save time and resources. In response, we introduce TrackNET, a recurrent neural network specifically designed for track...
Tracking charged particles resulting from collisions in the presence of strong magnetic field is an important and challenging problem. Reconstructing the tracks from the hits created by those generated particles on the detector layers via ionization energy deposits is traditionally achieved through Kalman filters that scale worse than linearly as the number of hits grow. To improve efficiency...
The ALICE Time Projection Chamber (TPC) is the detector with the highest data rate of the ALICE experiment at CERN and is the central detector for tracking and particle identification. Efficient online computing such as clusterization and tracking are mainly performed on GPU's with throughputs of approximately 900 GB/s. Clusterization itself has a well known background with a variety of...
Polarized cryo-targets and polarized photon beams are widely used in experiments at Jefferson Lab. Traditional methods for maintaining the optimal polarization involve manual adjustments throughout data taking-- an approach that is prone to inconsistency and human error. Implementing machine learning-based control systems can improve the stability of the polarization without relying on human...
ALICE is the dedicated heavy ion experiment at the LHC at CERN and records lead-lead collisions at a rate of up to 50 kHz.
The detector with the highest data rate of up to 3.4 TB/s is the TPC.
ALICE performs the full online TPC processing corresponding to more than 95% of the total workload on GPUs, and when there is no beam in the LHC, the online computing farm's GPUs are used to speed up...
ATLAS is one of the two general-purpose experiments at the Large Hadron
Collider (LHC), aiming to detect a wide variety of physics processes. Its
trigger system plays a key role in selecting the events that are detected,
filtering them down from the 40 MHz bunch crossing rate to the 1 kHz rate at
which they are committed to storage. The ATLAS trigger works in two stages,
Level- 1 and the...
In preparation for the High Luminosity LHC (HL-LHC) run, the CMS collaboration is working on an ambitious upgrade project for the first stage of its online selection system: the Level-1 Trigger. The upgraded system will use powerful field-programmable gate arrays (FPGA) processors connected by a high-bandwidth network of optical fibers. The new system will access highly granular calorimeter...
The General Triplet Track Fit (GTTF) is a generalization of the Multiple Scattering Triplet Fit [NIMA 844 (2017) 135] to additionally take hit uncertainties into account. This makes it suitable for use in collider experiments, where the position uncertainties of hits dominate for high momentum tracks. Since the GTTF is based on triplets of hits that can be processed independently, the fit is...
The CBM experiment is expected to run with a data rate exceeding 500 GB/s even after averaging. At this rate storing raw detector data is not feasible and an efficient online reconstruction is instead required. GPUs have become essential for HPC workloads. The higher memory bandwidth and parallelism of GPUs can provide significant speedups over traditional CPU applications. These properties...
The PANDA experiment has been designed to incorporate software triggers and online data processing. Although PANDA may not surpass the largest experiments in terms of raw data rates, designing and developing the processing pipeline and software platform for this purpose is still a challenge. Given the uncertain timeline for PANDA and the constantly evolving landscape of computing hardware, our...
For the HL-LHC upgrade of the ATLAS TDAQ system, a heterogeneous computing farm
deploying GPUs and/or FPGAs is under study, together with the use of modern
machine learning algorithms such as Graph Neural Networks (GNNs). We present a
study on the reconstruction of tracks in the ATLAS Inner Tracker using GNNs on
FPGAs for the Event Filter system. We explore each of the steps in a...
Abstract: The LHCb collaboration is planning an upgrade (LHCb "Upgrade-II") to collect data at an increased instantaneous luminosity (a factor of 7.5 larger than the current one). LHCb relies on a complete real-time reconstruction of all collision events at LHC-Point 8, which will have to cope with both the luminosity increase and the introduction of correspondingly more granular and complex...
We present the preparation, deployment, and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS experiment Global Trigger (GT) test crate FPGAs during LHC Run 3. The GT makes the final decision whether to readout or discard the data from each LHC collision, which occur at a rate of 40 MHz, within a 50 ns latency. The Neural Network makes a prediction...
For the upcoming HL-LHC upgrade of the ATLAS experiment, the deployment of GPU
or FPGA co-processors within the online Event Filter system is being studied as
a measure to increase throughput and save power. End-to-end track
reconstruction pipelines are currently being developed using commercially
available FPGA accelerator cards. These utilize FPGA base partitions, drivers
and runtime...
This work presents FPGA-RICH, an FPGA-based online partial particle identification system for the NA62 experiment utilizing AI techniques. Integrated between the readout of the Ring Imaging Cherenkov detector (RICH) and the low-level trigger processor (L0TP+) , FPGA-RICH implements a fast pipeline to process in real-time the RICH raw hit data stream, producing trigger-primitives containing...
Particle detectors at accelerators generate large amount of data, requiring analysis to derive insights. Collisions lead to signal pile up, where multiple particles produce signals in the same detector sensors, complicating individual signal identification. This contribution describes the implementation of a deep learning algorithm on a Versal ACAP device for improved processing via...
The ATLAS experiment at CERN is constructing upgraded system
for the "High Luminosity LHC", with collisions due to start in
2029. In order to deliver an order of magnitude more data than
previous LHC runs, 14 TeV protons will collide with an instantaneous
luminosity of up to 7.5 x 10e34 cm^-2s^-1, resulting in much higher pileup and
data rates than the current experiment was designed to...
The CMS Level-1 Trigger Data Scouting (L1DS) introduces a novel approach within the CMS Level-1 Trigger (L1T), enabling the acquisition and processing of L1T primitives at the 40 MHz LHC bunch-crossing (BX) rate. The target for this system is the CMS Phase-2 Upgrade for the High Luminosity phase of LHC, harnessing the improved Phase-2 L1T design, where tracker and high-granularity calorimeter...
The Next Generation Triggers project (NextGen in short) is a five-year collaboration across ATLAS and CMS (with contributions from LHCb and ALICE) and the Experimental Physics, Theoretical Physics, and Information Technology Departments of CERN to research and develop new ideas and technologies for the experiment trigger systems for HL-LHC and beyond. After more than a year of preparation in...
The new generation of high-energy physics experiments plans to acquire data in streaming mode. With this approach, it is possible to access the information of the whole detector (organized in time slices) for optimal and lossless triggering of data acquisition. Each front-end channel sends data to the processing node via TCP/IP when an event is detected. The data rate in large detectors is...
The High-Luminosity LHC upgrade will have a new trigger system that utilizes detailed information from the calorimeter, muon and track finder subsystems at the bunch crossing rate, which enables the final stage of the Level-1 Trigger, the Global Trigger (GT), to use high-precision trigger objects. In addition to cut-based algorithms, novel machine-learning-based algorithms will be employed in...
In this talk we present the HIGH-LOW project, which addresses the need to achieve sustainable computational systems and to develop new Artificial Intelligence (AI) applications that cannot be implemented with the current hardware solutions due to the requirements of high-speed response and power constraints. In particular we are focused on the several computing solutions at the Large Hadron...
The Mu2e experiment at Fermilab aims to observe coherent neutrinoless conversion of a muon to an electron in the field of an aluminum nucleus, with a sensitivity improvement of 10,000 times over current limits.
The Mu2e Trigger and Data Acquisition System (TDAQ) uses \emph{otsdaq} framework as the online Data Acquisition System (DAQ) solution.
Developed at Fermilab, \emph{otsdaq} integrates...
