[en] The latest measurements about b quark fragmentation functions are reviewed, taking into account the differences in methods and in what is actually measured

[en] The available experimental measurements for g_bb-bar and g_cc-bar are reviewed, including some very recent results. The measurements are combined having particular care in the cross-correlations between the two quantities. The combined values can be used to rescale the central value and the error for R_b

[en] The CMS Collaboration has chosen for the Level 2/3 Trigger a design which uses a farm of commodity PCs. A selection based on the CMS Tracker, not used at Level 1, can be performed on all of the data sent to Level 2/3. The performance is comparable to the performance achieved with offline reconstruction code

[en] A review of the recent developments on data analysis techniques for the upcoming LHC experiments is presented, with the description of early tests ('Data Challenges'), which are being performed before the start-up, to validate the overall design

[en] The ALEPH Collaboration [1] took data at the LEP (CERN) electron-positron collider in the period 1989-2000, producing more than 300 scientific papers. While most of the Collaboration activities stopped in the last years, the data collected still has physics potential, with new theoretical models emerging, which ask checks with data at the Z and WW production energies. An attempt to revive and preserve the ALEPH Computing Environment is presented; the aim is not only the preservation of the data files (usually called bit preservation), but of the full environment a physicist would need to perform brand new analyses. Technically, a Virtual Machine approach has been chosen, using the VirtualBox platform. Concerning simulated events, the full chain from event generators to physics plots is possible, and reprocessing of data events is also functioning. Interactive tools like the DALI event display can be used on both data and simulated events. The Virtual Machine approach is suited for both interactive usage, and for massive computing using Cloud like approaches.

[en] The high-luminosity program has seen numerous extrapolations of its needed computing resources that each indicate the need for substantial changes if the desired HL-LHC physics program is to be supported within the current level of computing resource budgets. Drivers include large increases in event complexity (leading to increased processing time and analysis data size) and trigger rates needed (5-10 fold increases) for the HL-LHC program. The CMS experiment has recently undertaken an effort to merge the ideas behind short-term and long-term resource models in order to make easier and more reliable extrapolations to future needs. Near term computing resource estimation requirements depend on numerous parameters: LHC uptime and beam intensities; detector and online trigger performance; software performance; analysis data requirements; data access, management, and retention policies; site characteristics; and network performance. Longer term modeling is affected by the same characteristics, but with much larger uncertainties that must be considered to understand the most interesting handles for increasing the "physics per computing dollar" of the HL-LHC. In this presentation, we discuss the current status of long term modeling of the CMS computing resource needs for HL-LHC with emphasis on techniques for extrapolations, uncertainty quantification, and model results. We illustrate potential ways that high-luminosity CMS could accomplish its desired physics program within today's computing budgets.

[en] The Mass Storage System installed at the INFN-CNAF Tier-1 is one of the biggest hierarchical storage facilities in Europe. It currently provides storage resources for about 12% of all LHC data, as well as for other experiments. The Grid Enabled Mass Storage System (GEMSS) is the current solution implemented at CNAF and it is based on a custom integration between a high performance parallel file system (General Parallel File System, GPFS) and a tape management system for long-term storage on magnetic media (Tivoli Storage Manager, TSM). Data access to Grid users is being granted since several years by the Storage Resource Manager (StoRM), an implementation of the standard SRM interface, widely adopted within the WLCG community. The evolving requirements from the LHC experiments and other users are leading to the adoption of more flexible methods for accessing the storage. These include the implementation of the so-called storage federations, i.e. geographically distributed federations allowing direct file access to the federated storage between sites. A specific integration between GEMSS and Xrootd has been developed at CNAF to match the requirements of the CMS experiment. This was already implemented for the ALICE use case, using ad-hoc Xrootd modifications. The new developments for CMS have been validated and are already available in the official Xrootd builds. This integration is currently in production and appropriate large scale tests have been made. In this paper we present the Xrootd solutions adopted for ALICE, CMS, ATLAS and LHCb to increase the availability and optimize the overall performance.

[en] The INFN Tier-1 located at CNAF in Bologna (Italy) is a center of the WLCG e-Infrastructure, supporting the 4 major LHC collaborations and more than 30 other INFN-related experiments. After multiple tests towards elastic expansion of CNAF compute power via Cloud resources (provided by Azure, Aruba and in the framework of the HNSciCloud project), and building on the experience gained with the production quality extension of the Tier-1 farm on remote owned sites, the CNAF team, in collaboration with experts from the ALICE, ATLAS, CMS, and LHCb experiments, has been working to put in production a solution of an integrated HTC+HPC system with the PRACE CINECA center, located nearby Bologna. Such extension will be implemented on the Marconi A2 partition, equipped with Intel Knights Landing (KNL) processors. A number of technical challenges were faced and solved in order to successfully run on low RAM nodes, as well as to overcome the closed environment (network, access, software distribution, …) that HPC systems deploy with respect to standard GRID sites. We show preliminary results from a large scale integration effort, using resources secured via the successful PRACE grant N. 2018194658, for 30 million KNL core hours.

[en] Minimising time and cost is key to exploit private or commercial clouds. This can be achieved by increasing setup and operational efficiencies. The success and sustainability are thus obtained reducing the learning curve, as well as the operational cost of managing community-specific services running on distributed environments. The greater beneficiaries of this approach are communities willing to exploit opportunistic cloud resources. DODAS builds on several EOSC-hub services developed by the INDIGO-DataCloud project and allows to instantiate on-demand container-based clusters. These execute software applications to benefit of potentially “any cloud provider”, generating sites on demand with almost zero effort. DODAS provides ready-to-use solutions to implement a “Batch System as a Service” as well as a BigData platform for a “Machine Learning as a Service”, offering a high level of customization to integrate specific scenarios. A description of the DODAS architecture will be given, including the CMS integration strategy adopted to connect it with the experiment’s HTCondor Global Pool. Performance and scalability results of DODAS-generated tiers processing real CMS analysis jobs will be presented. The Instituto de Física de Cantabria and Imperial College London use cases will be sketched. Finally a high level strategy overview for optimizing data ingestion in DODAS will be described.

[en] 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.