with constant dns failure when running xdp drv, flow direction and ntuple rules need to be hardened.

ATLAS deneyi tarafından kaydedilen yaklaşık 2 TB'lık veriye aşağıdaki bağlantıdan ulaşabilirsiniz. Veri analiziyle ilgilenenler için güzel bir fırsat. C /Root yardımıyla NTuple formatındaki veriyi kolaylıkla analiz edebilirsiniz. Değişkenlerin korelasyon matrislerini çıkarın, makine öğrenme için verileri kullanın, dağılımları bir fonksiyona fit edip interpolasyon/ekstrapolasyon çalışması yapın, vs. Daha nice farklı şeyler yapabilirsiniz.

NTuples are simplified data structures used to store parameters of interest from particle collision events in a spreadsheet-like format. atlas-outreach-data-tools.gi… Here is their CROWN 👑 Framework called KingMaker.... Crown (C -based ROot Workflow for N-tuples) The C -based ROot Workflow for N-tuples (CROWN) framework is a fast way, of converting CMS NanoAOD samples into analysis N-tuples. crown.readthedocs.io/en/late… NanoAOD NanoAOD is a plain, Ntuple-like format, readable with bare ROOT and containing per-event information needed in most generic analyses. NanoAOD is not a CMSSW EDM format. However, several EDM features are available in this simplified format too. twiki.cern.ch/twiki/bin/view… KingMaker KingMaker is a workflow management for producing ntuples with the CROWN framework. The workflow management is based on law (github.com/riga/law), which uses luigi (github.com/spotify/luigi) as the backend. Kingmaker is used to orchestrate the production of ntuples and friend trees for the CROWN framework. Kingmaker takes care of building all required CROWN executables, submitting jobs to a batch system and writing the output to a remote storage. On top of that, Kingmaker can be used to generate FriendTrees, which can be used to store additional information to extend the ntuples. crown.readthedocs.io/en/late… Data Aggregation System (DAS) Go client GO implementation of DAS (Data Aggregation System) client for CMS data-services Command line interface for DAS (dasgoclient) github.com/dmwm/dasgoclient twiki.cern.ch/twiki/bin/view… DataTier represents the dataformat of the dataset. We are mostly interested in NANOAOD(SIM) and MINIAOD(SIM) which are tailored for analyses. The USER datatier represents anything that a user can produce. twiki.cern.ch/twiki/bin/view… This file is an example of an (overcomplete) law configuration file github.com/riga/law/blob/mas… PHYSLITE The PHYSLITE format represents an advancement in ATLAS data analysis, transitioning from Run 2 through to Run 4. It is designed to efficiently manage and analyze the large datasets generated in the ATLAS experiment and stands out for its streamlined approach. Developed during Run 3, PHYSLITE incorporates calibrated objects and selections with lower transverse momentum (pT) thresholds, coupled with elements like machine learning scores. This format not only minimizes the need for storing extensive calibration data but also reduces CPU usage, optimizing the overall analysis workflow. atlas-outreach-data-tools.gi… PHYSLITE - A new reduced common data format for ATLAS PHYSLITE will be the main format for ATLAS at the High Luminosity LHC (HL-LHC) and aims to serve 80% of all physics analyses. To simplify analysis workloads and further reduce disk usage it is designed to largely replace user-defined analysis n-tuples and consequently contains pre-calibrated objects. Various forms of validations are in place to ensure correct functionality for users. Developments continue towards HL-LHC to improve the PHYSLITE format further. cds.cern.ch/record/2870350/f… Athena ATLAS Software Framework documentation Athena is the primary software framework used in ATLAS. It integrates a wide array of tools and software packages specifically designed for ATLAS. It plays an important role in data reconstruction and analysis due to its ability to efficiently process large volumes of data, translating complex particle interactions into analyzable information. Athena includes almost all the tools used for digitization and reconstruction processes, making it essential to the overall success of data interpretation in ATLAS experiments. atlas-software.docs.cern.ch/… Simulation tools atlas-outreach-data-tools.gi… Could this tie into the Athena Agenda and advancing the Apollo program for biodefense?

In the new LHCb workflow there is no offline reconstruction any more. The trigger does the final selection and thus it is essential that analysis get in their nTuple the exact quantity that was used in the trigger. If the trigger changes, FunTuple changes.

FunTuple the algorithm that harvests @LHCbExperiment Run 3 data or simulation and saves the relevant information into a ROOT nTuple (now TTree, RNtuple under development).

no i constantly yap about how the normal old fashioned way of using root to analyze an ntuple is much more versatile

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The default is ROOT flat ntuple. We also provide a hdf5 converter to get .h5 format.

Lim [n->inf] ntuple F*CK ruZZia

Good that we are not competitors ;) - Anyway, 'AI' will be only able to make it faster by programming specific filters tied to the attacks into specific (hardware) filters, e.g. rx-ntuple directly filtering on the NIC FPGA.

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* the deg::Integer you dont necessarily need the Integer there, types in method args are just for dispatch or documentation, everything will be inferred just the same w/o it * you can use do-block syntax to make the map/ntuple a little easier to read eg stackoverflow.com/a/67519603

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Best you can do is `Tuple[Array["size", ...]]` for the input and `Array["out"]` for the output. Python's type system doesn't include an NTuple type unfortunately. Worth noting that something like this is a limitation of essentially every practical type system: you can always...

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