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HL-LHC will confront the WLCG community with enormous data storage, management and access challenges. These are as much technical as economical. In the WLCG-DOMA Access working group, members of the experiments and site managers have explored different models for data access and storage strategies to reduce cost and complexity, taking into account the boundary conditions given by our community.Several of these scenarios have been evaluated quantitatively, such as the Data Lake model and incremental improvements of the current computing model with respect to resource needs, costs and operational complexity.To better understand these models in depth, analysis of traces of current data accesses and simulations of the impact of new concepts have been carried out. In parallel, evaluations of the required technologies took place. These were done in testbed and production environments at small and large scale.We will give an overview of the activities and results of the working group, describe the models and summarise the results of the technology evaluation focusing on the impact of storage consolidation in the form of Data Lakes, where the use of streaming caches has emerged as a successful approach to reduce the impact of latency and bandwidth limitation.We will describe the experience and evaluation of these approaches in different environments and usage scenarios. In addition we will present the results of the analysis and modelling efforts based on data access traces of the experiments.

Throughout the last decade the Open Science Grid (OSG) has been fielding requests from user communities, resource owners, and funding agencies to provide information about utilization of OSG resources. Requested data include traditional accounting - core-hours utilized - as well as users certificate Distinguished Name, their affiliations, and field of science. The OSG accounting service, Gratia, developed in 2006, is able to provide this information and much more. However, with the rapid expansion and transformation of the OSG resources and access to them, we are faced with several challenges in adapting and maintaining the current accounting service. The newest changes include, but are not limited to, acceptance of users from numerous university campuses, whose jobs are flocking to OSG resources, expansion into new types of resources (public and private clouds, allocation-based HPC resources, and GPU farms), migration to pilot-based systems, and migration to multicore environments. In order to have a scalable, sustainable and expandable accounting service for the next few years, we are embarking on the development of the next-generation OSG accounting service, GRACC, that will be based on open-source technology and will be compatible with the existing system. It will consist of swappable, independent components, such as Logstash, Elasticsearch, Grafana, and RabbitMQ, that communicate through a data exchange. GRACC will continue to interface EGI and XSEDE accounting services and provide information in accordance with existing agreements. We will present the current architecture and working prototype.

Following the success of the XRootd-based US CMS data federation, the AAA project investigated extensions of the federation architecture by developing two sample implementations of an XRootd, disk-based, caching proxy. The first one simply starts fetching a whole file as soon as a file open request is received and is suitable when completely random file access is expected or it is already known that a whole file be read. The second implementation supports on-demand downloading of partial files. Extensions to the Hadoop Distributed File System have been developed to allow for an immediate fallback to network access when local HDFS storage fails to provide the requested block. Both cache implementations are in pre-production testing at UCSD.

Bosco is a software project developed by the Open Science Grid to help scientists better utilize their on-campus computing resources. Instead of submitting jobs through a dedicated gatekeeper, as most remote submission mechanisms use, it uses the built-in SSH protocol to gain access to the cluster. By using a common access method, SSH, we are able to simplify the interaction with the cluster, making the submission process more user friendly. Additionally, it does not add any extra software to be installed on the cluster making Bosco an attractive option for the cluster administrator. In this paper, we will describe Bosco, the personal supercomputing assistant, and how Bosco is used by researchers across the U.S. to manage their computing workflows. In addition, we will also talk about how researchers are using it, including an unique use of Bosco to submit CMS reconstruction jobs to an opportunistic XSEDE resource.

Databases are used in many software components of HEP computing, from monitoring and job scheduling to data storage and processing. It is not always clear at the beginning of a project if a problem can be handled by a single server, or if one needs to plan for a multi-server solution. Before a scalable solution is adopted, it helps to know how well it performs in a single server case to avoid situations when a multi-server solution is adopted mostly due to sub-optimal performance per node. This paper presents comparison benchmarks of popular open source database management systems. As a test application we use a user job monitoring system based on the Glidein workflow management system used in the CMS Collaboration.

CMS is using a tiered setup of dedicated computing resources provided by sites distributed over the world and organized in WLCG. These sites pledge resources to CMS and are preparing them especially for CMS to run the experiment's applications. But there are more resources available opportunistically both on the GRID and in local university and research clusters which can be used for CMS applications. We will present CMS' strategy to use opportunistic resources and prepare them dynamically to run CMS applications. CMS is able to run its applications on resources that can be reached through the GRID, through EC2 compliant cloud interfaces. Even resources that can be used through ssh login nodes can be harnessed. All of these usage modes are integrated transparently into the GlideIn WMS submission infrastructure, which is the basis of CMS' opportunistic resource usage strategy. Technologies like Parrot to mount the software distribution via CVMFS and xrootd for access to data and simulation samples via the WAN are used and will be described. We will summarize the experience with opportunistic resource usage and give an outlook for the restart of LHC data taking in 2015.

The CMS analysis computing model was always relying on jobs running near the data, with data allocation between CMS compute centers organized at management level, based on expected needs of the CMS community. While this model provided high CPU utilization during job run times, there were times when a large fraction of CPUs at certain sites were sitting idle due to lack of demand, all while Terabytes of data were never accessed. To improve the utilization of both CPU and disks, CMS is moving toward controlled overflowing of jobs from sites that have data but are oversubscribed to others with spare CPU and network capacity, with those jobs accessing the data through real time Xrootd streaming over WAN. The major limiting factor for remote data access is the ability of the source storage system to serve such data, so the number of jobs accessing it must be carefully controlled. The CMS approach to this is to implement the overflowing by means of glideinWMS, a Condor based pilot system, and by providing the WMS with the known storage limits and let it schedule jobs within those limits. This paper presents the detailed architecture of the overflow-enabled glideinWMS system, together with operational experience of the past 6 months.

OSG has been operating for a few years at UCSD a glideinWMS factory for several scientific communities, including CMS analysis, HCC and GLOW. This setup worked fine, but it had become a single point of failure. OSG thus recently added another instance at Indiana University, serving the same user communities. Similarly, CMS has been operating a glidein factory dedicated to reprocessing activities at Fermilab, with similar results. Recently, CMS decided to host another glidein factory at CERN, to increase the availability of the system, both for analysis, MC and reprocessing jobs. Given the large overlap between this new factory and the three factories in the US, and given that CMS represents a significant fraction of glideins going through the OSG factories, CMS and OSG formed a common operations team that operates all of the above factories. The reasoning behind this arrangement is that most operational issues stem from Grid-related problems, and are very similar for all the factory instances. Solving a problem in one instance thus very often solves the problem for all of them. This paper presents the operational experience of how we address both the social and technical issues of running multiple instances of a glideinWMS factory with operations staff spanning multiple time zones on two continents.

During spring and summer of 2011, CMS deployed Xrootd-based access for all US T1 and T2 sites. This allows for remote access to all experiment data on disk in the US. It is used for user analysis, visualization, running of jobs at computing sites when data is not available at local sites, and as a fail-over mechanism for data access in jobs. Monitoring of this Xrootd infrastructure is implemented on three levels. Basic service and data availability checks are performed by Nagios probes. The second level uses Xrootd's “summary data” stream; this data is aggregated from all sites and fed into a MonALISA service providing visualization and storage. The third level uses Xrootd's “detailed monitoring” stream, which includes detailed information about users, opened files and individual data transfers. A custom application was developed to process this information. It currently provides a real-time view of the system usage and can store data into ROOT files for detailed analysis. Detailed monitoring allows us to determine dataset popularity and to detect abuses of the system, including sub-optimal usage of the Xrootd protocol and the ROOT prefetching mechanism.

This paper describes a programme to study the computing model in CMS after the next long shutdown near the end of the decade.