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At least 109 records · Page 6

A study of multi-jet production in association with an electroweak vector boson

Here, we consider the production of a single Z or W boson in association with jets at the LHC. We compute the corresponding cross sections by matching NLO QCD predictions with the Herwig++ and Pythia8 parton showers, and by merging all of the underlying matrix elements with up to two light partons at the Born level. We compare our results with several 7-TeV measurements by the ATLAS and CMS collaborations, and overall we find a good agreement between theory and data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Extending the Fermi -LAT data processing pipeline to the grid

The Data Handling Pipeline ("Pipeline") has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data quality monitoring quantities, reconstruction and routine analysis of all data received from the satellite and to deliver science products to the collaboration and the Fermi Science Support Center. Aside from the reconstruction of raw data from the satellite (Level 1), data reprocessing and various event-level analyses are also reasonably heavy loads on the pipeline and computing resources. These other loads, unlike Level 1, can run continuously for weeks or months at a time. Additionally, it receives heavy use in performing production Monte Carlo tasks.

ASTRO↗

Optimizing the performance and structure of the D0 Collie confidence limit evaluator

D0 Collie is a program used to perform limit calculations based on ensembles of pseudo-experiments ('PEs'). Since the application of this program to the crucial Higgs mass limit is quite CPU intensive, it has been deemed important to carefully review this program, with an eye toward identifying and implementing potential performance improvements. At the same time, we identify any coding errors or opportunities for potential structural (or algorithm) improvement discovered in the course of gaining sufficient understanding of the workings of Collie to sensibly explore for optimizations. Based on a careful analysis of the program, a series of code changes with potential for improving performance has been identified. The implementation and evaluation of the most important parts of this series has been done, with gratifying speedup results. The bottom line: We have identified and implemented changes leading to a factor of 2.19 speedup in the example program provided, and expected to translate to a factor of roughly 4 speedup in typical realistic usage.

99 GENERAL AND MISCELLANEOUS↗

First Experiences with LHC Grid Computing and Distributed Analysis

In this presentation the experiences of the LHC experiments using grid computing were presented with a focus on experience with distributed analysis. After many years of development, preparation, exercises, and validation the LHC (Large Hadron Collider) experiments are in operations. The computing infrastructure has been heavily utilized in the first 6 months of data collection. The general experience of exploiting the grid infrastructure for organized processing and preparation is described, as well as the successes employing the infrastructure for distributed analysis. At the end the expected evolution and future plans are outlined.

99 GENERAL AND MISCELLANEOUS↗

Arachne - A web-based event viewer for MINERvA

Neutrino interaction events in the MINERvA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERvA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Antinucleus-Nucleus Cross Sections Implemented in Geant4

Cross sections of antinucleus ({bar p}, {bar d}, {bar t}, {sup 3}{ovr He}, {sup 4}{ovr He}) interactions with nuclei in the energy range 100 MeV/c to 1000 GeV/c per antinucleon are calculated in the Glauber approximation which provides good description of all known {bar p}Across sections. The results were obtained using a new parameterization of the total and elastic {bar p}p cross sections. Simple parameterizations of the antinucleus-nucleus cross sections are proposed for use in estimating the efficiency of antinucleus detection and tracking in cosmic rays and accelerator experiments. These parameterizations are implemented in the Geant4 toolkit.

43 PARTICLE ACCELERATORS↗

3D Technology for intelligent trackers

At Super-LHC luminosity it is expected that the standard suite of level 1 triggers for CMS will saturate. Information from the tracker will be needed to reduce trigger rates to satisfy the level 1 bandwidth. Tracking trigger modules which correlate information from closely-spaced sensor layers to form an on-detector momentum filter are being developed by several groups. We report on a trigger module design which utilizes three dimensional integrated circuit technology incorporating chips which are connected both to the top and bottom sensor, providing the ability to filter information locally. A demonstration chip, the VICTR, has been submitted to the Chartered/Tezzaron two-tier 3D run coordinated by Fermilab. We report on the 3D design concept, the status of the VICTR chip and associated sensor integration utilizing oxide bonding.

99 GENERAL AND MISCELLANEOUS↗

ACE3P Computations of Wakefield Coupling in the CLIC Two-Beam Accelerator

The Compact Linear Collider (CLIC) provides a path to a multi-TeV accelerator to explore the energy frontier of High Energy Physics. Its novel two-beam accelerator concept envisions rf power transfer to the accelerating structures from a separate high-current decelerator beam line consisting of power extraction and transfer structures (PETS). It is critical to numerically verify the fundamental and higher-order mode properties in and between the two beam lines with high accuracy and confidence. To solve these large-scale problems, SLAC's parallel finite element electromagnetic code suite ACE3P is employed. Using curvilinear conformal meshes and higher-order finite element vector basis functions, unprecedented accuracy and computational efficiency are achieved, enabling high-fidelity modeling of complex detuned structures such as the CLIC TD24 accelerating structure. In this paper, time-domain simulations of wakefield coupling effects in the combined system of PETS and the TD24 structures are presented. The results will help to identify potential issues and provide new insights on the design, leading to further improvements on the novel CLIC two-beam accelerator scheme.

43 PARTICLE ACCELERATORS↗

Performance of GeantV EM Physics Models

The recent progress in parallel hardware architectures with deeper vector pipelines or many-cores technologies brings opportunities for HEP experiments to take advantage of SIMD and SIMT computing models. Launched in 2013, the GeantV project studies performance gains in propagating multiple particles in parallel, improving instruction throughput and data locality in HEP event simulation on modern parallel hardware architecture. Due to the complexity of geometry description and physics algorithms of a typical HEP application, performance analysis is indispensable in identifying factors limiting parallel execution. In this report, we will present design considerations and preliminary computing performance of GeantV physics models on coprocessors (Intel Xeon Phi and NVidia GPUs) as well as on mainstream CPUs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Vision on the Status and Evolution of HEP Physics Software Tools

This paper represents the vision of the members of the Fermilab Scientific Computing Division's Computational Physics Department (SCD-CPD) on the status and the evolution of various HEP software tools such as the Geant4 detector simulation toolkit, the Pythia and GENIE physics generators, and the ROOT data analysis framework. The goal of this paper is to contribute ideas to the Snowmass 2013 process toward the composition of a unified document on the current status and potential evolution of the physics software tools which are essential to HEP.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Celeritas Midterm SciDAC Report

Celeritas is a new Monte Carlo (MC) code that helps satisfy the increasing demand for high energy physics (HEP) detector simulation, using Graphics Processing Unit (GPU) hardware on high performance computing (HPC) systems to model Large Hadron Collider (LHC) experiments and beyond. This report details the project’s progress midway through its SciDAC funding period, highlighting the first complete implementation of standard electromagnetic (EM) physics on GPUs, initial results for performance and scalability on Leadership Computing Facilities (LCFs), and preliminary integration into the CMS and ATLAS experiments. By integrating HEP domain knowledge with expertise in MC transport, Celeritas has catalyzed a shift in the HEP community’s perception of GPU platforms as the future for HPC simulations.

97 MATHEMATICS AND COMPUTING↗

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Herner, K.↗

Spack-Based Packaging and Development for HEP

The art event-based analysis framework is used by multiple Intensity Frontier and other experiments and projects in High Energy Physics (HEP). A system of tools and scripts based around a Fermilab-originated package management system called UNIX Product Support (UPS) has evolved to provide development, packaging, release management, and distribution of the art suite, related experimental software and external dependencies in relocatable binary form. The existing system has limitations in environments such as macOS with System Integrity Protection (SIP) enabled and the various High Performance Computing (HPC) systems that the field of HEP is increasingly looking to leverage. This has led to a search for other ways of providing experiments with a packaging and build system that meets their needs. We describe our efforts to develop a packaging and release management system based on the Spack HPC package management tool to replace the existing UPS-based system. We additionally describe a companion system: SpackDev and cetmodules, allowing simultaneous development of multiple HEP software packages in a consistent environment. A successful implementation of the intended system would have applicability across HEP rather than merely to the users of the art framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics

High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapidly increasing fraction of floating point computing power in leadership-class computing facilities and traditional data centers coming from new accelerator architectures, such as GPUs. HEP experiments are now faced with the untenable prospect of rewriting millions of lines of x86 CPU code, for the increasingly dominant architectures found in these computational accelerators. This task is made more challenging by the architecture-specific languages and APIs promoted by manufacturers such as NVIDIA, Intel and AMD. Producing multiple, architecture-specific implementations is not a viable scenario, given the available person power and code maintenance issues. The Portable Parallelization Strategies team of the HEP Center for Computational Excellence is investigating the use of Kokkos, SYCL, OpenMP, std::execution::parallel and alpaka as potential portability solutions that promise to execute on multiple architectures from the same source code, using representative use cases from major HEP experiments, including the DUNE experiment of the Long Baseline Neutrino Facility, and the ATLAS and CMS experiments of the Large Hadron Collider. This cross-cutting evaluation of portability solutions using real applications will help inform and guide the HEP community when choosing their software and hardware suites for the next generation of experimental frameworks. We present the outcomes of our studies, including performance metrics, porting challenges, API evaluations, and build system integration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server

Abstract With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for example, have provided astounding improvements in extracting complex signatures from data and are now widely used in a variety of applications, such as particle jet classification in high energy physics (HEP). However, GNNs also come with an enormous computational penalty that requires the use of GPUs to maintain reasonable throughput. At shared computing facilities, such as those used by physicists at Fermi National Accelerator Laboratory (Fermilab), methodical resource allocation and high throughput at the many-user scale are key to ensuring that resources are being used as efficiently as possible. These facilities, however, primarily provide CPU-only nodes, which proves detrimental to time-to-insight and computational throughput for workflows that include machine learning inference. In this work, we describe how a shared computing facility can use the NVIDIA Triton Inference Server to optimize its resource allocation and computing structure, recovering high throughput while scaling out to multiple users by massively parallelizing their machine learning inference. To demonstrate the effectiveness of this system in a realistic multi-user environment, we use the Fermilab Elastic Analysis Facility augmented with the Triton Inference Server to provide scalable and high-throughput access to a HEP-specific GNN and report on the outcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗