1,717 research outputs found
Designing Computing System Architecture and Models for the HL-LHC era
This paper describes a programme to study the computing model in CMS after
the next long shutdown near the end of the decade.Comment: Submitted to proceedings of the 21st International Conference on
Computing in High Energy and Nuclear Physics (CHEP2015), Okinawa, Japa
Moving the California distributed CMS xcache from bare metal into containers using Kubernetes
The University of California system has excellent networking between all of
its campuses as well as a number of other Universities in CA, including
Caltech, most of them being connected at 100 Gbps. UCSD and Caltech have thus
joined their disk systems into a single logical xcache system, with worker
nodes from both sites accessing data from disks at either site. This setup has
been in place for a couple years now and has shown to work very well.
Coherently managing nodes at multiple physical locations has however not been
trivial, and we have been looking for ways to improve operations. With the
Pacific Research Platform (PRP) now providing a Kubernetes resource pool
spanning resources in the science DMZs of all the UC campuses, we have recently
migrated the xcache services from being hosted bare-metal into containers. This
paper presents our experience in both migrating to and operating in the new
environment
Moving the California distributed CMS XCache from bare metal into containers using Kubernetes
The University of California system maintains excellent networking between its campuses and a number of other Universities in California, including Caltech, most of them being connected at 100 Gbps. UCSD and Caltech Tier2 centers have joined their disk systems into a single logical caching system, with worker nodes from both sites accessing data from disks at either site. This successful setup has been in place for the last two years. However, coherently managing nodes at multiple physical locations is not trivial and requires an update on the operations model used. The Pacific Research Platform (PRP) provides Kubernetes resource pool spanning resources in the science demilitarized zones (DMZs) in several campuses in California and worldwide. We show how we migrated the XCache services from bare-metal deployments into containers using the PRP cluster. This paper presents the reasoning behind our hardware decisions and the experience in migrating to and operating in a mixed environment
Any Data, Any Time, Anywhere: Global Data Access for Science
Data access is key to science driven by distributed high-throughput computing
(DHTC), an essential technology for many major research projects such as High
Energy Physics (HEP) experiments. However, achieving efficient data access
becomes quite difficult when many independent storage sites are involved
because users are burdened with learning the intricacies of accessing each
system and keeping careful track of data location. We present an alternate
approach: the Any Data, Any Time, Anywhere infrastructure. Combining several
existing software products, AAA presents a global, unified view of storage
systems - a "data federation," a global filesystem for software delivery, and a
workflow management system. We present how one HEP experiment, the Compact Muon
Solenoid (CMS), is utilizing the AAA infrastructure and some simple performance
metrics.Comment: 9 pages, 6 figures, submitted to 2nd IEEE/ACM International Symposium
on Big Data Computing (BDC) 201
Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events
The High-Luminosity Large Hadron Collider at CERN will be characterized by
greater pileup of events and higher occupancy, making the track reconstruction
even more computationally demanding. Existing algorithms at the LHC are based
on Kalman filter techniques with proven excellent physics performance under a
variety of conditions. Starting in 2014, we have been developing
Kalman-filter-based methods for track finding and fitting adapted for many-core
SIMD processors that are becoming dominant in high-performance systems.
This paper summarizes the latest extensions to our software that allow it to
run on the realistic CMS-2017 tracker geometry using CMSSW-generated events,
including pileup. The reconstructed tracks can be validated against either the
CMSSW simulation that generated the hits, or the CMSSW reconstruction of the
tracks. In general, the code's computational performance has continued to
improve while the above capabilities were being added. We demonstrate that the
present Kalman filter implementation is able to reconstruct events with
comparable physics performance to CMSSW, while providing generally better
computational performance. Further plans for advancing the software are
discussed
Software Challenges For HL-LHC Data Analysis
The high energy physics community is discussing where investment is needed to
prepare software for the HL-LHC and its unprecedented challenges. The ROOT
project is one of the central software players in high energy physics since
decades. From its experience and expectations, the ROOT team has distilled a
comprehensive set of areas that should see research and development in the
context of data analysis software, for making best use of HL-LHC's physics
potential. This work shows what these areas could be, why the ROOT team
believes investing in them is needed, which gains are expected, and where
related work is ongoing. It can serve as an indication for future research
proposals and cooperations
ROOT for the HL-LHC: data format
This document discusses the state, roadmap, and risks of the foundational
components of ROOT with respect to the experiments at the HL-LHC (Run 4 and
beyond). As foundational components, the document considers in particular the
ROOT input/output (I/O) subsystem. The current HEP I/O is based on the TFile
container file format and the TTree binary event data format. The work going
into the new RNTuple event data format aims at superseding TTree, to make
RNTuple the production ROOT event data I/O that meets the requirements of Run 4
and beyond
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
ROOT is an object-oriented C++ framework conceived in the high-energy physics
(HEP) community, designed for storing and analyzing petabytes of data in an
efficient way. Any instance of a C++ class can be stored into a ROOT file in a
machine-independent compressed binary format. In ROOT the TTree object
container is optimized for statistical data analysis over very large data sets
by using vertical data storage techniques. These containers can span a large
number of files on local disks, the web, or a number of different shared file
systems. In order to analyze this data, the user can chose out of a wide set of
mathematical and statistical functions, including linear algebra classes,
numerical algorithms such as integration and minimization, and various methods
for performing regression analysis (fitting). In particular, ROOT offers
packages for complex data modeling and fitting, as well as multivariate
classification based on machine learning techniques. A central piece in these
analysis tools are the histogram classes which provide binning of one- and
multi-dimensional data. Results can be saved in high-quality graphical formats
like Postscript and PDF or in bitmap formats like JPG or GIF. The result can
also be stored into ROOT macros that allow a full recreation and rework of the
graphics. Users typically create their analysis macros step by step, making use
of the interactive C++ interpreter CINT, while running over small data samples.
Once the development is finished, they can run these macros at full compiled
speed over large data sets, using on-the-fly compilation, or by creating a
stand-alone batch program. Finally, if processing farms are available, the user
can reduce the execution time of intrinsically parallel tasks - e.g. data
mining in HEP - by using PROOF, which will take care of optimally distributing
the work over the available resources in a transparent way
Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV
Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio
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