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The transition of the Worldwide Large Hadron Collider Computing Grid (WLCG) storage services to dual-stack IPv6/IPv4 is almost complete; all Tier-1 and 94% of Tier-2 storage are IPv6 enabled. While most data transfers now use IPv6, a significant number of IPv4 transfers still occur even when both endpoints support IPv6. This paper presents the ongoing efforts of the HEPiX IPv6 working group to steer WLCG toward IPv6-only services by investigating and fixing the obstacles to the use of IPv6 and identifying cases where IPv4 is used when IPv6 is available. Removing IPv4 use is essential for the long-term agreed goal of IPv6-only access to resources within WLCG, thus eliminating the complexity and security concerns associated with dual-stack services. We present our achievements and ongoing challenges as we navigate the final stages of the transition from IPv4 to IPv6 within WLCG.

The current computing models from LHC experiments indicate that much larger resource increases would be required by the HL-LHC era (2026+) than those that technology evolution at a constant budget could bring. Since worldwide budget for computing is not expected to increase, many research activities have emerged to improve the performance of the LHC processing software applications, as well as to propose more efficient resource deployment scenarios and data management techniques, which might reduce this expected increase of resources. The massively increasing amounts of data to be processed leads to enormous challenges for HEP storage systems, networks and the data distribution to end-users. These challenges are particularly important in scenarios in which the LHC data would be distributed from small numbers of centers holding the experiment’s data. Enabling data locality relative to computing tasks via local caches on sites seems a very promising approach to hide transfer latencies while reducing the deployed storage space and number of replicas overall. However, this highly depends on the workflow I/O characteristics and available network across sites. A crucial assessment of how the experiments are accessing and using the storage services deployed in WLCG sites, to evaluate and simulate the benefits for several of the new emerging proposals within WLCG/HSF. Studies on access and usage of storage, data access and popularity studies for the CMS workflows executed in the Spanish Tier-1 (PIC) and Tier-2 (CIEMAT) sites supporting CMS activities are reviewed in this report, based on local and experiment monitoring data, spanning more than one year. This is of relevance for simulation of data caches for end-user analysis data, as well as identifying potential areas for storage savings.

The ATLAS Spanish Tier-1 and Tier-2s have more than 15 years of experience in the deployment and development of LHC computing components and their successful operations. The sites are already actively participating in, and even coordinating, emerging R&D computing activities and developing new computing models needed for the Run3 and HighLuminosity LHC periods. In this contribution, we present details on the integration of new components, such as High Performance Computing resources to execute ATLAS simulation workflows. The development of new techniques to improve efficiency in a cost-effective way, such as storage and CPU federations is shown in this document. Improvements in data organization, management and access through storage consolidations (“data-lakes”), the use of data caches, and improving experiment data catalogs, like Event Index, are explained in this proceeding. The design and deployment of new analysis facilities using GPUs together with CPUs and techniques like Machine Learning will also be presented. Tier-1 and Tier-2 sites, are, and will be, contributing to significant R&D in computing, evaluating different models for improving performance of computing and data storage capacity in the High-Luminosity LHC era.

The increase in the scale of LHC computing during Run 3 and Run 4 (HL-LHC) will certainly require radical changes to the computing models and the data processing of the LHC experiments. The working group established by WLCG and the HEP Software Foundation to investigate all aspects of the cost of computing and how to optimise them has continued producing results and improving our understanding of this process. In particular, experiments have developed more sophisticated ways to calculate their resource needs, we have a much more detailed process to calculate infrastructure costs. This includes studies on the impact of HPC and GPU based resources on meeting the computing demands. We have also developed and perfected tools to quantitatively study the performance of experiments workloads and we are actively collaborating with other activities related to data access, benchmarking and technology cost evolution. In this contribution we expose our recent developments and results and outline the directions of future work.

In view of the increasing computing needs for the HL-LHC era, the LHC experiments are exploring new ways to access, integrate and use non-Grid compute resources. Accessing and making efficient use of Cloud and High Performance Computing (HPC) resources present a diversity of challenges for the CMS experiment. In particular, network limitations at the compute nodes in HPC centers prevent CMS pilot jobs to connect to its central HTCondor pool in order to receive payload jobs to be executed. To cope with this limitation, new features have been developed in both HTCondor and the CMS resource acquisition and workload management infrastructure. In this novel approach, a bridge node is set up outside the HPC center and the communications between HTCondor daemons are relayed through a shared file system. This conforms the basis of the CMS strategy to enable the exploitation of the Barcelona Supercomputing Center (BSC) resources, the main Spanish HPC site. CMS payloads are claimed by HTCondor condor_startd daemons running at the nearby PIC Tier-1 center and routed to BSC compute nodes through the bridge. This fully enables the connectivity of CMS HTCondor-based central infrastructure to BSC resources via the PIC HTCondor pool. Other challenges include building custom singularity images with CMS software releases, bringing conditions data to payload jobs, and custom data handling between BSC and PIC. This report describes the initial technical prototype, its deployment and tests, and future steps. A key aspect of the technique described in this contribution is that it could be universally employed in similar network-restrictive HPC environments elsewhere.

The increase in the scale of LHC computing expected for Run 3 and even more so for Run 4 (HL-LHC) over the next ten years will certainly require radical changes to the computing models and the data processing of the LHC experiments. Translating the requirements of the physics programmes into computing resource needs is a complicated process and subject to significant uncertainties. For this reason, WLCG has established a working group to develop methodologies and tools intended tocharacterise the LHC workloads, better understand their interaction with the computing infrastructure, calculate their cost in terms of resources and expenditure and assist experiments, sites and the WLCG project in the evaluation of their future choices. This working group started in November 2017 and has about 30 active participants representing experiments and sites. In this contribution we expose the activities, the results achieved and the future directions.