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  1. The volume of data moving through a network increases with new scientific experiments and simulations. Network bandwidth requirements also increase proportionally to deliver data within a certain time frame. We observe that a significant portion of the popular dataset is transferred multiple times to different users as well as to the same user for various reasons. In-network data caching for the shared data has shown to reduce the redundant data transfers and consequently save network traffic volume. In addition, overall application performance is expected to improve with in-network caching because access to the locally cached data results in lower latency.more »This paper shows how much data was shared over the study period, how much network traffic volume was consequently saved, and how much the temporary in-network caching increased the scientific application performance. It also analyzes data access patterns in applications and the impacts of caching nodes on the regional data repository. From the results, we observed that the network bandwidth demand was reduced by nearly a factor of 3 over the study period.« less
  2. Abstract Jet classification is an important ingredient in measurements and searches for new physics at particle colliders, and secondary vertex reconstruction is a key intermediate step in building powerful jet classifiers. We use a neural network to perform vertex finding inside jets in order to improve the classification performance, with a focus on separation of bottom vs. charm flavor tagging. We implement a novel, universal set-to-graph model, which takes into account information from all tracks in a jet to determine if pairs of tracks originated from a common vertex. We explore different performance metrics and find our method to outperformmore »traditional approaches in accurate secondary vertex reconstruction. We also find that improved vertex finding leads to a significant improvement in jet classification performance.« less
  3. The experiments at the Large Hadron Collider (LHC) rely upon a complex distributed computing infrastructure (WLCG) consisting of hundreds of individual sites worldwide at universities and national laboratories, providing about half a billion computing job slots and an exabyte of storage interconnected through high speed networks. Wide Area Networking (WAN) is one of the three pillars (together with computational resources and storage) of LHC computing. More than 5 PB/day are transferred between WLCG sites. Monitoring is one of the crucial components of WAN and experiments operations. In the past years all experiments have invested significant effort to improve monitoring and integratemore »networking information with data management and workload management systems. All WLCG sites are equipped with perfSONAR servers to collect a wide range of network metrics. We will present the latest development to provide the 3D force directed graph visualization for data collected by perfSONAR. The visualization package allows site admins, network engineers, scientists and network researchers to better understand the topology of our Research and Education networks and it provides the ability to identify nonreliable or/and nonoptimal network paths, such as those with routing loops or rapidly changing routes.« less
  4. Biscarat, C. ; Campana, S. ; Hegner, B. ; Roiser, S. ; Rovelli, C.I. ; Stewart, G.A. (Ed.)
    The High Luminosity Large Hadron Collider provides a data challenge. The amount of data recorded from the experiments and transported to hundreds of sites will see a thirty fold increase in annual data volume. A systematic approach to contrast the performance of different Third Party Copy (TPC) transfer protocols arises. Two contenders, XRootD-HTTPS and the GridFTP are evaluated in their performance for transferring files from one server to another over 100Gbps interfaces. The benchmarking is done by scheduling pods on the Pacific Research Platform Kubernetes cluster to ensure reproducible and repeatable results. This opens a future pathway for network testingmore »of any TPC transfer protocol.« less
  5. Biscarat, C. ; Campana, S. ; Hegner, B. ; Roiser, S. ; Rovelli, C.I. ; Stewart, G.A. (Ed.)
    CMS is tackling the exploitation of CPU resources at HPC centers where compute nodes do not have network connectivity to the Internet. Pilot agents and payload jobs need to interact with external services from the compute nodes: access to the application software (CernVM-FS) and conditions data (Frontier), management of input and output data files (data management services), and job management (HTCondor). Finding an alternative route to these services is challenging. Seamless integration in the CMS production system without causing any operational overhead is a key goal. The case of the Barcelona Supercomputing Center (BSC), in Spain, is particularly challenging, duemore »to its especially restrictive network setup. We describe in this paper the solutions developed within CMS to overcome these restrictions, and integrate this resource in production. Singularity containers with application software releases are built and pre-placed in the HPC facility shared file system, together with conditions data files. HTCondor has been extended to relay communications between running pilot jobs and HTCondor daemons through the HPC shared file system. This operation mode also allows piping input and output data files through the HPC file system. Results, issues encountered during the integration process, and remaining concerns are discussed.« less