Conveners
Distributed Computing Services
- Conrad Steenberg (CalTech)
Distributed Computing Services
- Rob Kennedy (FNAL)
Distributed Computing Services
- Oxana Smirnova (CERN)
M. Branco
(CERN)
9/27/04, 2:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
As part of the ATLAS Data Challenges 2 (DC2), an automatic production system was
introduced and with it a new data management component.
The data management tools used for previous Data Challenges were built as separate
components from the existing Grid middleware. These tools relied on a database of its
own which acted as a replica catalog.
With the extensive use of Grid technology...
M. Ernst
(DESY)
9/27/04, 2:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
The LHC needs to achieve reliable high performance access to vastly distributed storage resources across the
network. USCMS has worked with Fermilab-CD and DESY-IT on a storage service that was deployed at several
sites. It provides Grid access to heterogeneous mass storage systems and synchronization between them. It
increases resiliency by insulating clients from storage and network...
L. Lueking
(FERMILAB)
9/27/04, 2:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
A high performance system has been assembled using standard web components to deliver
database information to a large number (thousands?) of broadly distributed clients.
The CDF Experiment at Fermilab is building processing centers around the world
imposing a high demand load on their database repository. For delivering read-only
data, such as calibrations, trigger information and run...
Dirk Duellmann
9/27/04, 3:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
While there are differences among the LHC experiments in their views of the role of
databases and their deployment, there is relatively widespread agreement on a number
of principles:
1. Physics codes will need access to database-resident data. The need for database
access is not confined to middleware and services: physics-related data will reside
in databases.
2. ...
O. Smirnova
(Lund University, Sweden)
9/27/04, 3:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
The NorduGrid middleware, ARC, has integrated support for querying and
registering to Data Indexing services such as the Globus Replica Catalog
and Globus Replica Location Server. This support allows one to use these
Data Indexing services for for example brokering during job-submission,
automatic registration of files and many other things. This
integrated support is complemented by a...
J-P. Baud
(CERN)
9/27/04, 3:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
LCG-2 is the collective name for the set of middleware released for
use on the LHC Computing Grid in December 2003. This middleware,
based on LCG-1, had already several improvements in the Data
Management area. These included the introduction of the Grid File
Access Library(GFAL), a POSIX-like I/O Interface, along with MSS
integration via the Storage Resource...
A. Hanushevsky
(SLAC)
9/27/04, 4:30โฏPM
Track 4 - Distributed Computing Services
oral presentation
As the BaBar experiment shifted its computing model to a ROOT-based
framework, we undertook the development of a high-performance file server
as the basis for a fault-tolerant storage environment whose ultimate goal
was to minimize job failures due to server failures. Capitalizing on our
five years of experience with extending Objectivity's Advanced
Multithreaded Server (AMS), elements...
E. Hjort
(LAWRENCE BERKELEY LABORATORY)
9/27/04, 4:50โฏPM
Track 4 - Distributed Computing Services
oral presentation
The STAR experiment utilizes two major computing facilities for its data processing
needs - the RCF at Brookhaven and the PDSF at LBNL/NERSC. The sharing of data
between these facilities utilizes data grid services for file replication, and the
deployment of these services was accomplished in conjunction with the Particle
Physics Data Grid (PPDG). For STAR's 2004 run it will be...
Ofer RIND
9/27/04, 5:10โฏPM
Track 4 - Distributed Computing Services
oral presentation
Providing Grid applications with effective access to large volumes of data residing
on a multitude of storage systems with very different characteristics prompted the
introduction of storage resource managers (SRM). Their purpose is to provide
consistent and efficient wide-area access to storage resources unconstrained by
their particular implementation (tape, large disk arrays,...
C. CIOFFI
(Oxford University)
9/27/04, 5:30โฏPM
Track 4 - Distributed Computing Services
oral presentation
The LHCb experiment needs to store all the information about the datasets and their
processing history of recorded data resulting from particle collisions at the LHC
collider at CERN as well as of simulated data.
To achieve this functionality a design based on data warehousing techniques was
chosen, where several user-services can be implemented and optimized individually
without...
K. Nienartowicz
(CERN)
9/27/04, 5:50โฏPM
Track 4 - Distributed Computing Services
oral presentation
Data management is one of the cornerstones in the distributed production computing
environment that the EGEE project aims to provide for a European e-Science
infrastructure. We have designed a set of services based on previous experience in
other Grid projects, trying to address the requirements of our user communities.
In this paper we summarize the most fundamental requirements and...
R. Kennedy
(FERMI NATIONAL ACCELERATOR LABORATORY)
9/27/04, 6:10โฏPM
Track 4 - Distributed Computing Services
oral presentation
SAMGrid is the shared data handling framework of the two large Fermilab
Run II collider experiments: DZero and CDF. In production since 1999 at D0, and
since mid-2004 at CDF, the SAMGrid framework has been adapted over time to
accommodate a variety of storage solutions and configurations, as well as the
differing data processing models of these two experiments. This has been...
Maria Girone
9/29/04, 2:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
This presentation will summarise the deployment experience gained
with POOL during the first larger LHC experiments data challenges
performed. In particular we discuss the storage access
performance and optimisations, the integration issues with grid
middleware services such as the LCG Replica Location Service
(RLS) and the LCG Replica Manager and experience with the POOL
proposed...
E. Laure
(CERN)
9/29/04, 2:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
The aim of the EGEE (Enabling Grids for E-Science in Europe) is to
create a reliable and dependable European Grid infrastructure for
e-Science. The objective of the Middleware Re-engineering and Integration
Research Activity is to provide robust middleware components,
deployable on several platforms and operating systems, corresponding
to the core Grid services for resource access, data...
C. Steenberg
(California Institute of Technology)
9/29/04, 2:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
Clarens enables distributed, secure and high-performance access to the
worldwide data storage, compute, and information Grids being constructed in
anticipation of the needs of the Large Hadron Collider at CERN. We report on
the rapid progress in the development of a second server implementation in
the Java language, the evolution of a peer-to-peer network of Clarens
servers, and general...
Birger KOBLITZ
(CERN)
9/29/04, 3:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
The ARDA project was started in April 2004 to support
the four LHC experiments (ALICE, ATLAS, CMS and LHCb)
in the implementation of individual
production and analysis environments based on the EGEE middleware.
The main goal of the project is to allow a fast feedback between the
experiment and the middleware development teams via the
construction and the usage of end-to-end...
F. Rademakers
(CERN)
9/29/04, 3:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
The ALICE experiment and the ROOT team have developed a Grid-enabled version of PROOF that allows
efficient parallel processing of large and distributed data samples. This system has been integrated with the
ALICE-developed AliEn middleware. Parallelism is implemented at the level of each local cluster for efficient
processing and at the Grid level, for optimal workload management of...
T. Barrass
(CMS, UNIVERSITY OF BRISTOL)
9/29/04, 3:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
CMS currently uses a number of tools to transfer data which, taken together, form
the basis of a heterogenous datagrid. The range of tools used, and the directed,
rather than optimised nature of CMS recent large scale data challenge required the
creation of a simple infrastructure that allowed a range of tools to operate in a
complementary way.
The system created comprises a...
9/29/04, 4:30โฏPM
Track 4 - Distributed Computing Services
oral presentation
SAM was developed as a data handling system for Run II at Fermilab. SAM is a
collection of services, each described by metadata. The metadata are modeled on a
relational database, and implemented in ORACLE. SAM, originally deployed in
production for the D0 Run II experiment, has now been also deployed at CDF and is
being commissioned at MINOS. This illustrates that the metadata...
E. Neilsen
(FERMI NATIONAL ACCELERATOR LABORATORY)
9/29/04, 4:50โฏPM
Track 4 - Distributed Computing Services
oral presentation
The lattice gauge theory community produces large volumes of
data. Because the data produced by completed computations form the
basis for future work, the maintenance of archives of existing data
and metadata describing the provenance, generation parameters, and
derived characteristics of that data is essential not only as a
reference, but also as a basis for future work. Development of...
Richard Mount
(SLAC)
9/29/04, 5:10โฏPM
Track 4 - Distributed Computing Services
oral presentation
9/30/04, 2:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
The ATLAS experiment uses a tiered data Grid architecture that enables
possibly overlapping subsets, or replicas, of the original set to be
located across the ATLAS collaboration. The full set of experiment
data is located at a single Tier 0 site, and then subsets of the data
are located at national Tier 1 sites, smaller subsets at smaller
regional Tier 2 sites, and so on. In order to...
Jerome LAURET
(BROOKHAVEN NATIONAL LABORATORY)
9/30/04, 2:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
While many success stories can be told as a product of the Grid middleware
developments, most of the existing systems relying on workflow and job execution are
based on integration of self-contained production systems interfacing with a given
scheduling component or portal, or directly uses the base component of the Grid
middleware (globus-job-run, globus-job-submit). However, such systems...
R. Cavanaugh
(UNIVERSITY OF FLORIDA)
9/30/04, 2:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
A grid consists of high-end computational, storage, and network resources that,
while known a priori, are dynamic with respect to activity and availability.
Efficient co-scheduling of requests to use grid resources must adapt to this
dynamic environment while meeting administrative policies. We discusses
the necessary requirements of such a scheduler and introduce a distributed...
9/30/04, 3:00โฏPM
Track 4 - Distributed Computing Services
oral presentation
The R-GMA (Relational Grid Monitoring Architecture) was developed within the EU
DataGrid project, to bring the power of SQL to an information and monitoring system
for the grid. It provides producer and consumer services to both publish and
retrieve information from anywhere within a grid environment. Users within a
Virtual Organization may define their own tables dynamically into...
M. Sgaravatto
(INFN Padova)
9/30/04, 3:20โฏPM
Track 4 - Distributed Computing Services
oral presentation
Resource management and scheduling of distributed, data-driven
applications in a Grid environment are challenging problems. Although
significant results were achieved in the past few years, the
development and the proper deployment of generic, reliable, standard
components present issues that still need to be completely
solved. Interested domains include workload management,...
B K. Kim
(UNIVERSITY OF FLORIDA),
M. Mambelli
(University of Chicago)
9/30/04, 3:40โฏPM
Track 4 - Distributed Computing Services
oral presentation
Grid computing involves the close coordination of many different sites which offer
distinct computational and storage resources to the Grid user community. The
resources at each site need to be monitored continuously. Static and dynamic site
information need to be presented to the user community in a simple and efficient
manner.
This paper will present both the design and...
I. Legrand
(CALTECH)
9/30/04, 4:30โฏPM
Track 4 - Distributed Computing Services
oral presentation
The MonALISA (MONitoring Agents in A Large Integrated Services Architecture) system
is a scalable Dynamic Distributed Services Architecture which is based on the mobile
code paradigm.
An essential part of managing a global system, like the Grids, is a monitoring system
that is able to monitor and track the many site facilities, networks, and all the
task in progress, in real time....
N. De Bortoli
(INFN - NAPLES (ITALY))
9/30/04, 4:50โฏPM
Track 4 - Distributed Computing Services
oral presentation
GridICE is a monitoring service for the Grid, it measures
significant Grid related resources parameters in order to analyze
usage, behavior and performance of the Grid and/or to detect and
notify fault situations, contract violations, and user-defined
events. In its first implementation, the notification service
relies on a simple model based on a pre-defined set of events.
The growing...
D. Smith
(STANFORD LINEAR ACCELERATOR CENTER)
9/30/04, 5:10โฏPM
Track 4 - Distributed Computing Services
oral presentation
The BaBar experiment has migrated its event store from an
objectivity based system to a system using ROOT-files, and along
with this has developed a new bookkeeping design. This bookkeeping
now combines data production, quality control, event store
inventory, distribution of BaBar data to sites and user analysis in
one central place, and is based on collections of data stored as...
M. Sanchez-Garcia
(UNIVERSITY OF SANTIAGO DE COMPOSTELA)
9/30/04, 5:30โฏPM
Track 4 - Distributed Computing Services
oral presentation
The LHCb Data Challenge 04 includes the simulation of over 200 M
simulated events using distributed computing resources on N sites and
extending along 3 months. To achieve this goal a dedicated Production
grid (DIRAC) has been deployed. We will present the Job
Monitoring and Accounting services developed to follow the status of
the production along its way and to evaluate the results at...
E. Efstathiadis
(BROOKHAVEN NATIONAL LABORATORY)
9/30/04, 5:50โฏPM
Track 4 - Distributed Computing Services
oral presentation
As a PPDG cross-team joint project, we proposed to study, develop,
implement and evaluate a set of tools that allow Meta-Schedulers to
take advantage of consistent information (such as information needed
for complex decision making mechanisms) across both local and/or Grid
Resource Management Systems (RMS).
We will present and define the requirements and schema by which one
can...
A. TSAREGORODTSEV
(CNRS-IN2P3-CPPM, MARSEILLE)
9/30/04, 6:10โฏPM
Track 4 - Distributed Computing Services
oral presentation
DIRAC is the LHCb distributed computing grid infrastructure for MC
production and analysis. Its architecture is based on a set of distributed
collaborating services. The service decomposition broadly follows the ARDA
project proposal, allowing for the possibility of interchanging the EGEE/ARDA
and DIRAC components in the future. Some components developed outside the
DIRAC project are...
