Sezione di Padova

The CMS experiment will produce several Pbytes of data every year, to be distributed over many computing centers geographically distributed in different countries. Analysis of this data will be also performed in a distributed way, using grid infrastructure. CRAB (CMS Remote Analysis Builder) is a specific tool, designed and developed by the CMS collaboration, that allows a transparent access to distributed data to end physicist. Very limited knowledge of underlying technicalities are required to the user. CRAB interacts with the local user environment, the CMS Data Management services and with the Grid middleware. It is able to use WLCG, gLite and OSG middleware. CRAB has been in production and in routine use by end-users since Spring 2004. It has been extensively used in studies to prepare the Physics Technical Design Report (PTDR) and in the analysis of reconstructed event samples generated during the Computing Software and Analysis Challenge (CSA06). This involved generating thousands of jobs per day at peak rates. In this paper we discuss the current implementation of CRAB, the experience with using it in production and the plans to improve it in the immediate future.

Job execution and management is one of the most important functionality provided by every modern Grid middleware. In this paper we describe how the problem of job management has been addressed in the gLite middleware by means of the CREAM and CEMonitor services. CREAM (Computing Resource Execution and Management) provides a job execution and management capability for Grid systems, while CEMonitor is a generalpurpose asynchronous event notification framework. Both services expose a Web Service interface allowing conforming clients to submit, manage and monitor computational jobs to a Local Resource Management System. PACS: 89.20.Ff Computer Science and Technology Published by SIS-Pubblicazioni

... E-mail: glite-jobmgmt-devel@lists.infn.it 1 INFN Padova, Via Marzolo 8, I-35131 Padova, Italy 2 INFN-CNAF, Viale Berti Pichat 6/2, I-40127 Bologna Italy 3 INFN Milano, Via Celoria 16, I-20133 Milano, Italy 4 INFN Catania, Via Santa Sofia 64, I-95123, Italy Abstract. ...

Abstract:- When dealing with the concurrent access from a multitude of clients to petabyte-scale data repositories, high performance, fault tolerance, robustness, and scalability are four very important issues. This work describes the architecture and the choices done in designing the xrootd file access system. The first goal of the system was to provide access to over 10^7 files representing several petabytes of experimental physics data. This work addresses the high demand data access needs of modern physics experiments, such as the BaBar experiment at SLAC, and covers method and tools useful to any other field in which reliability, performance and scalability in data access are a primary issue. Key-Words:- Scalability, Fault tolerance, load balancing, peer to peer, XROOTD, TXNetFile, ROOT 1- From a storage system to a data access architecture The BaBar experiment [1] at the Stanford Linear Accelerator Center 1 produces a huge amount of data to be accessed by a high number of anal...

When dealing with the concurrent access from a multitude of clients to petabyte-scale data repositories, high performance, fault tolerance, robustness, and scalability are four very important issues. This paper describes the choices and the work done to address the client side of high demand data access needs of modern physics experiments, such as the BaBar experiment at SLAC, and of any other field in which a reliable data access is a primary issue. For this purpose a highly scalable architecture has been designed and deployed which allows thousands of batch jobs and interactive sessions to effectively access the data repositories with as few fails as possible. ROOT REMOTE DATA ACCESS ROOT provides a remote file access mechanism via a TCP/IP-based data server daemon known as rootd, and its only purpose is to serve opaque data. rootd and the ROOT framework allow an analysis job to get access to local or remote files in a transparent way without any change to the source code. In fact...