The increased footprint foreseen for Run-3 and HL-LHC data will soon expose the limits of currently available storage and CPU resources. Data formats are already optimized according to the processing ...chain for which they are designed. ATLAS events are stored in ROOT-based reconstruction output files called Analysis Object Data (AOD), which are then processed within the derivation framework to produce Derived AOD (DAOD) files. Numerous DAOD formats, tailored for specific physics and performance groups, have been in use throughout the ATLAS Run-2 phase. In view of Run-3, ATLAS has changed its analysis model, which entailed a significant reduction of the existing DAOD flavors. Two new formats, unfiltered, skimmable on read and designed to meet the requirements of the majority of the analysis workflows, have been proposed as replacements: DAOD_PHYS and DAOD_PHYSLITE, a smaller format containing already calibrated physics objects. As ROOT-based formats, they natively support four lossless compression algorithms: lzma, lz4, zlib and zstd. In this study, the effects of different compression settings on file size, compression time, compression factor and reading speed are investigated considering both DAOD_PHYS and DAOD_PHYSLITE formats. Moreover, the impact of the AutoFlush parameter controlling how in-memory data structures are serialized to ROOT files, has been evaluated. This study yields new quantitative results that can serve as a paradigm on how to make compression decisions for different ATLAS use cases. As an example, for both DAOD_PHYS and DAOD_PHYSLITE, the lz4 library exhibits the fastest reading speed, but results in the largest files, whereas the lzma algorithm provides larger compression factors at the cost of significantly slower reading speeds. In addition, guidelines for setting appropriate AutoFlush values are outlined.
For Run 3, ATLAS redesigned its offline software, Athena, so that the main workflows run completely multithreaded. The resulting substantial reduction in the overall memory requirements allows for ...better use of machines with many cores. This note will discuss the performance achieved by the multithreaded reconstruction, the process of migrating the large ATLAS code base, and tools and techniques that were useful in debugging threading-related problems.
For HEP event processing, data is typically stored in column-wise synchronized containers, such as most prominently ROOT’s TTree, which have been used for several decades to store by now over 1 ...exabyte. These containers can combine row-wise association capabilities needed by most HEP event processing frameworks (e.g. Athena for ATLAS) with column-wise storage, which typically results in better compression and more efficient support for many analysis use-cases. One disadvantage is that these containers, TTree in the HEP use-case, require to contain the same attributes for each entry/row (representing events), which can make extending the list of attributes very costly in storage, even if those are only required for a small subsample of events. Since the initial design, the ATLAS software framework features powerful navigational infrastructure to allow storing custom data extensions for subsamples of events in separate, but synchronized containers. This allows adding event augmentations to ATLAS standard data products (such as DAOD-PHYS or PHYSLITE) avoiding duplication of those core data products, while limiting their size increase. For this functionality, the framework does not rely on any associations made by the I/O technology (i.e. ROOT), however it supports TTree friends and builds the associated index to allow for analysis outside of the ATLAS framework. A prototype based on the Long-Lived Particle search is implemented and preliminary results with this prototype will be presented. At this point, augmented data are stored within the same file as the core data. Storing them in separate files will be investigated in future, as this could provide more flexibility, e.g. certain sites may only want a subset of several augmentations or augmentations can be archived to tape once their analysis is complete.
GPU Usage in ATLAS Reconstruction and Analysis Krasznahorkay, Attila; Leggett, Charles; Mete, Alaettin Serhan ...
EPJ Web of Conferences,
2020, Letnik:
245
Journal Article, Conference Proceeding
Recenzirano
Odprti dostop
With Graphical Processing Units (GPUs) and other kinds of accelerators becoming ever more accessible, High Performance Computing Centres all around the world using them ever more, ATLAS has to find ...the best way of making use of such accelerators in much of its computing.
Tests with GPUs – mainly with CUDA – have been performed in the past in the experiment. At that time the conclusion was that it was not advantageous for the ATLAS offline and trigger software to invest time and money into GPUs. However as the usage of accelerators has become cheaper and simpler in recent years, their re-evaluation in ATLAS’s offline software is warranted.
We show new results of using GPU accelerated calculations in ATLAS’s offline software environment using the ATLAS offline/analysis (xAOD) Event Data Model. We compare the performance and flexibility of a couple of the available GPU programming methods, and show how different memory management setups affect our ability to offload different types of calculations to a GPU efficiently.
Highlights from new physics searches with the ATLAS detector at the CERN Large Hadron Collider are presented. Results are based on the analysis of data collected in pp collisions at a center-of-mass ...energy of 7 TeV corresponding to integrated luminosities of 1-5 fb super(-1). No excess beyond the Standard Model expectations is observed.
The ATLAS detector is used to search for high-mass states, such as heavy charged gauge bosons (W'), decaying to a muon and a neutrino. Results are presented based on the analysis of pp collisions at ...a center-of-mass energy of 7 TeV corresponding to an integrated luminosity of 1.04 fb−1. No excess beyond standard model expectations is observed. A W' with sequential standard model couplings is excluded at 95% confidence level for masses below 1.98 TeV. Results from the muon channel are also combined with the electron channel to further extend the mass limit up to 2.15 TeV. This is the most stringent limit published to date.
We study the T odd correlations induced by CP violating anomalous top-quark couplings at both production and decay level in the process gg --> t t_bar --> (b mu+ nu_mu) (b_bar mu- nu_mu_bar). We ...consider several counting asymmetries at the parton level and find the ones with the most sensitivity to each of these anomalous couplings at the LHC.
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