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The ATLAS Spanish Tier-1 and Tier-2s have more than 18 years of experience in the deployment and development of LHC computing components and their successful operation. The sites are actively participating in, and in some cases coordinating, R&D computing activities in the LHC Run 3 and developing the computing models needed in the HL-LHC period. In this contribution, we present details on the integration of some components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way; and improvements in Data Organization, Management and Access through storage consolidations, the use of data caches, and improving experiment data catalogues, through contributions such as Event Index. The design and deployment of novel analysis facilities using GPUs together with CPUs and techniques like Machine Learning are also presented. ATLAS Tier-1 and Tier-2 sites in Spain, are, and will be, contributing to significant R&D in computing and evaluating different models for improving performance of computing and data storage capacity in the LHC High Luminosity era.

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.