Conveners
Track 1: Computing Technology for Physics Research
- Patricia Mendez Lorenzo (CERN)
- Gordon Watts (University of Washington (US))
Track 1: Computing Technology for Physics Research
- Gordon Watts (University of Washington (US))
- Patricia Mendez Lorenzo (CERN)
Track 1: Computing Technology for Physics Research
- Gordon Watts (University of Washington (US))
- Patricia Mendez Lorenzo (CERN)
Track 1: Computing Technology for Physics Research
- Gordon Watts (University of Washington (US))
- Patricia Mendez Lorenzo (CERN)
Track 1: Computing Technology for Physics Research
- Gordon Watts (University of Washington (US))
- Patricia Mendez Lorenzo (CERN)
Track 1: Computing Technology for Physics Research
- Patricia Mendez Lorenzo (CERN)
- Gordon Watts (University of Washington (US))
Track 1: Computing Technology for Physics Research
- Patricia Mendez Lorenzo (CERN)
- Gordon Watts (University of Washington (US))
Track 1: Computing Technology for Physics Research
- Gordon Watts (University of Washington (US))
- Patricia Mendez Lorenzo (CERN)
When it comes to number-crunching, C++ is at the core of HENP’s software. But while C++17 is old news, many of us did not get to use it yet. And why would we? This presentation introduces some of the main reasons to move to C++17 - focusing on performant, readable code and robust interfaces.
Where C++17 has many new features that help, C++20 might come as “your next C++11”, a major step...
NANOAOD is an event data format that has recently been commissioned by the CMS Collaboration to serve the needs of a substantial fraction of its physics analyses. The new format is about 20 times more compact than the MINIAOD format and only includes high level physics object information. NANOAOD is easily customisable for development activities, and supports standardised routines for content...
PyROOT is the name of ROOT’s Python bindings, which allow to access all the ROOT functionality implemented in C++ from Python. Thanks to the ROOT type system and the Cling C++ interpreter, PyROOT creates Python proxies for C++ entities on the fly, thus avoiding to generate static bindings beforehand.
PyROOT is in the process of being enhanced and modernised to meet the demands of the HEP...
During the past two years ROOT's analysis tools underwent a major renovation,
embracing a declarative approach.
This contribution explores the most recent developments of the implementation of
such approach, some real-life examples from LHC experiments as well as present
and future R&D lines.
After an introduction of the tool offering access to declarative analysis,
RDataFrame, the newly...
For two decades, ROOT brought its own graphics system abstraction based
on a graphics model inspired by the popular graphics systems available
at that time. (X11, OpenGL, Cocoa ...)
With the emergence of modern C++ and recent graphics systems based on client/server
models, it was time to redefined completely ROOT graphics.
This has been been done in the context of ROOT 7 which provides the...
Modern data processing (acquisition, storage and analysis) requires modern tools.
One of the problems shared by existing scientific software is "scripting" approach, when user writes an imperative script which describes the stages in which data should be processed. The main deficiency of such approach is the lack of possibility to automate the process. For example one usually needs script to...
As a data-intensive computing application, high-energy physics requires storage and computing for large amounts of data at the PB level. Performance demands and data access imbalances in mass storage systems are increasing. Specifically, on one hand, traditional cheap disk storage systems have been unable to handle high IOPS demand services. On the other hand, a survey found that only a very...
DODAS stands for Dynamic On Demand Analysis Service and is a Platform as a Service toolkit built around several EOSC-hub services designed to instantiate and configure on-demand container-based clusters over public or private Cloud resources. It automates the whole workflow from service provisioning to the configuration and setup of software applications. Therefore, such solution allows to use...
A large amount of data is produced by large scale scientific facilities in high energy physics (HEP) field. And distributed computing technologies has been widely used to process these data. In traditional computing model such as grid computing, computing job is usually scheduled to the sites where the input data was pre-staged in. This model will lead to some problems includ-ing low CPU...
Storage have been identified as the main challenge for the future distributed computing infrastructures: Particle Physics (HL-LHC, DUNE, Belle-II), Astrophysics and Cosmology (SKA, LSST). In particular, the High Luminosity LHC (HL-LHC) will begin operations in the year of 2026 with expected data volumes to increase by at least an order of magnitude as compared with the present systems....
The LHCb Upgrade experiment will start operations in LHC Run 3 from 2021 onwards. Owing to the five-times higher instantaneous luminosity and higher foreseen trigger efficiency, the LHCb Upgrade will collect signal yields per unit time approximately ten times higher than that of the current experiment, with pileup increasing by a factor of six. This contribution presents the changes in the...
The LHCb experiment will be upgraded for data taking in Run 3 and beyond and the instantaneous luminosity will in particular increase by a factor five. The lowest level trigger of the current experiment, a hardware-based trigger that has a hard limit of 1 MHz in its event output rate, will be removed. and replaced with a full software trigger. This new
trigger needs to sustain rates up 30 MHz...
The HL-LHC program has seen numerous extrapolations of its needed computing resources that each indicate the need for substantial changes if the desired HL-LHC physics program is to be supported within the current level of computing resource budgets. Drivers include detector upgrades, large increases in event complexity (leading to increased processing time and analysis data size) and trigger...
The ATLAS experiment produced so far hundreds of petabytes of data and expects to have one order of magnitude more in the future. This data are spread among hundreds of computing Grid sites around the world. The EventIndex is the complete catalogue of all ATLAS events, real and simulated, keeping the references to all permanent files that contain a given event in any processing stage. It...
Network monitoring is of great importance for every data acquisition system (DAQ), it ensures stable and uninterrupted data flow. However, when using standard tools such as Icinga, often homogeneity of the DAQ hardware is not exploited.
We will present the application of machine learning techniques to detect anomalies among network devices as well as connection instabilities. The former...
The increasing LHC luminosity in Run III and, consequently, the increased number of simultaneous proton-proton collisions (pile-up) pose significant challenges for the CMS experiment. These challenges will affect not only the data taking conditions, but also the data processing environment of CMS, which requires an improvement in the online triggering system to match the required detector...
The first LHCb upgrade will take data at an instantaneous luminosity of 2E33cm^{-2}s^{-1} starting in 2021. Due to the high rate of beauty and charm signals LHCb has chosen as its baseline to read out the entire detector into a software trigger running on commodity x86 hardware at the LHC collision frequency of 30MHz, where a full offline-quality reconstruction will be performed. In this talk...
The ATLAS software infrastructure has undergone several changes towards the adoption of Continuous Integration methodology to develop and test software. The users community can benefit from a CI environment in several ways: they can develop their custom analysis, build and test it using revision control services such as GitLab. By providing targeted official base images ATLAS enables users to...
Resources required for high-throughput computing in large-scale particle physics experiments face challenging demands both now and in the future. The growing exploration of machine learning algorithms in particle physics offers new solutions to simulation, reconstruction, and analysis. These new machine learning solutions often lead to increased parallelization and faster reconstructions...
The next generation of HPC and HTC facilities, such as Oak Ridge’s Summit, Lawrence Livermore’s Sierra, and NERSC's Perlmutter, show an increasing use of GPGPUs and other accelerators in order to achieve their high FLOP counts. This trend will only grow with exascale facilities such as A21. In general, High Energy Physics computing workflows have made little use of GPUs due to the relatively...
The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data obtained at unprecedented energy and rates. The TDAQ Controls system is the component that guarantees the smooth and synchronous operations of all the TDAQ components and provides the means to minimize the...
The ATLAS experiment at the LHC at CERN will move to use the Front-End Link eXchange (FELIX) system in a staged approach for LHC Run 3 (2021) and LHC Run 4 (2026). FELIX will act as the interface between the data acquisition; detector control and TTC (Timing, Trigger and Control) systems; and new or updated trigger and detector front-end electronics.
FELIX functions as a router between custom...
ATLAS production system called ProdSys2 is used during Run2 to define
and to organize workflows and to schedule, submit and execute payloads
in a distributed computing infrastructure. We design ProdSys2 to manage
all ATLAS workflows: data (re)processing, MC simulation, physics groups
analysis objects production, High Level Trigger processing, SW release
building and user analysis. It...
The Level-0 Muon Trigger system of the ATLAS experiment will undergo a full upgrade for HL-LHC to stand the challenging performances requested with the increasing instantaneous luminosity. The upgraded trigger system foresees to send RPC raw hit data to the off-detector trigger processors, where the trigger algorithms run on new generation of Field-Programmable Gate Arrays (FPGAs). The FPGA...
The CMS experiment has been designed with a two-level trigger system: the Level 1 Trigger, implemented on custom-designed electronics, and the High Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. A software trigger system requires a trade-off between the complexity of the algorithms running on the available computing resources,...
The next LHC Runs, nominally RunIII and RunIV, pose problems to the offline and computing systems in CMS. RunIV in particular will needs completely different solutions, given the current estimates of LHC conditions and Trigger estimates. We want to report on the R&D process CMS has a whole has established, in order to gain insight on the needs and the possible solutions for the 2020+ CMS computing.
Certifying the data recorded by the Compact Muon Solenoid (CMS) experiment at CERN which is usable for publication of physics results is a crucial and onerous task. Anomalies caused by detector malfunctioning or sub-optimal data processing are difficult to enumerate a priori and occur rarely, making it difficult to use classical supervised classification. We base out prototype towards the...
The hardware trigger L0 will be removed in LHCb upgrade I, and the software High Level Trigger have to process event at full LHC collision rate (30 MHz). This is a huge task, and delegating some low-level time-consuming tasks to FPGA accelerators can be very helpful in saving computing time that can be more usefully devoted to higher level tasks. In particular, the 2-D pixel geometry of the...
ROOT has several features which interact with libraries and require implicit header inclusion. This can be triggered by reading or writing data on disk, or user actions at the prompt. Often, the headers are immutable and reparsing is redundant. C++ Modules are designed to minimize the reparsing of the same header content by providing an efficient on-disk representation of C++ Code. ROOT has...
In particle physics, workflow management systems are primarily used as tailored solutions in dedicated areas such as Monte Carlo production. However, physicists performing data analyses are usually required to steer their individual workflows manually which is time-consuming and often leads to undocumented relations between particular workloads.
We present the luigi analysis workflow (law)...
RooFit is the statistical modeling and fitting package used in many big particle physics experiments to extract physical parameters from reduced particle collision data, e.g. the Higgs boson experiments at the LHC.
RooFit aims to separate particle physics model building and fitting (the users' goals) from their technical implementation and optimization in the back-end.
In this talk, we...
The LHCb detector will be upgraded in 2021, and due to the removal of the hardware-level trigger and the increase in the luminosity of the collisions, the conditions for a High Level Trigger 1 in software will become more challenging, requiring processing the full 30 MHz data-collision rate. The GPU High Level Trigger 1 is a framework that permits concurrent many-event execution targeting...
Artificial neural networks are becoming a standard tool for data analysis, but their potential remains yet to be widely used for hardware-level trigger applications. Nowadays, high-end FPGAs, as they are also often used in low-level hardware triggers, offer enough performance to allow for the inclusion of networks of considerable size into these system for the first time. Nevertheless, in the...
Nested data structures are critical for particle physics: it would be impossible to represent collision data as events containing arbitrarily many particles in a rectangular table (without padding or truncation, or without relational indirection). These data structures are usually constructed as class objects and arbitrary length sequences, such as vectors in C++ and lists in Python, and data...
Efficient random number generation with high quality statistical properties and exact reproducibility of Monte Carlo simulation are important requirements in many areas of computational science. VecRNG is a package providing pseudo-random number generation (pRNG) in the context of a new library VecMath. This library bundles up several general-purpose mathematical utilities, data structures...
Improving the computing performance of particle transport simulation is an important goal to address the challenges of HEP experiments in the coming decades (i.e. HL-LHC), as well as the needs of other fields (i.e. medical imaging and radiotherapy).
The GeantV prototype includes a new transport engine, based on track level parallelization by grouping a large number of tracks in flight into...
Deep Learning techniques have are being studied for different applications by the HEP community: in this talk, we discuss the case of detector simulation. The need for simulated events, expected in the future for LHC experiments and their High Luminosity upgrades, is increasing dramatically and requires new fast simulation solutions. We will describe an R&D activity within CERN openlab, aimed...
JANA2 is multi-threaded event reconstruction framework being developed for Experimental Nuclear Physics. It is an LDRD funded project that will be the successor of the original JANA framework. JANA2 is a near complete rewrite emphasizing C++ language features that have only become available since the C++11 standard. Successful and less-than-successful strategies employed in JANA and how they...
The Solenoidal Tracker at RHIC (STAR) is a multi-national supported experiment located at Brookhaven National Lab. The raw physics data captured from the detector is on the order of tens of PBytes per data acquisition campaign, which makes STAR fit well within the definition of a big data science experiment. The production of the data has typically run on standard nodes or on standard Grid...
The overlapping grid technique can be used to solve partial differential equations defined on complex computational domains. However, large-scale realistic applications using overlapping grid technique under distributed memory systems are not easy. The grid points do not meet point by point and interpolation is needed. Applications with millions of grid points may consist of many blocks. A...
