Science Grid This Week

September 14, 2005

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Calendar/Meetings

September 2005

4-17, CERN School of Computing 2005, Saint Malo, France

6-15, Second National Virtual Observatory Summer School, Aspen, Colorado

11-14, The Second Grid Applications and Middleware Workshop, Poznan, Poland

19-22, Fall 2005 Internet2 Member Meeting, Phildelphia, Pennsylvania

19-22, U.K. e-Science All Hands Meeting 2005, Nottingham, UK

19-22, 2nd International Conference on Grid Service Engineering and Management, Erfurt, Thuringia, Germany

21, International Workshop on Advanced Technologies for E-Learning and E-Science (ATELS '05), Compiégne, France

Full Calendar

Image of the Week

Illustration of grid architecture. (Click on image for larger version.)
Image and text courtesy of the GridCafé, CERN

The architecture of the grid is often described in terms of "layers," each providing a specific function. At the base of everything is the network, which assures the connectivity for the resources in the grid. On top of it lies the resource layer, which includes computers, storage systems, data catalogues, and even sensors such as telescopes. The middleware layer provides the tools that enable the various elements to participate in a unified grid environment. The application layer is highest, and includes all the different user applications, portals and development toolkits supporting the applications.

Statistic of the Week

750,000
Number of source lines of code in the middleware package gLite as of July 20, 2005. The source code is written in more than six different programming languages.
Source: CERN Courier

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RSS Headlines

Feature Story

PHENIX Experiment Uses Grid to Transfer 270 Terabytes of Data to Japan

A collision of gold nuclei as seen in the center of the PHENIX detector, with no magnetic field applied.
Image Courtesy PHENIX Collaboration

During the polarized proton-proton run that ended in June at the Relativistic Heavy Ion Collider at Brookhaven, grid tools were used by the PHENIX experiment to send recently acquired data to a regional computing center for the experiment in Japan. Brookhaven National Laboratory, on Long Island, New York, is home to the RHIC/ATLAS Computing Facility (RCF), which is the main computing center for experiments at RHIC and a Tier-1 computing center for ATLAS. The PHENIX regional computing center in Japan (CCJ) is at the RIKEN research centre on its Wako campus close to Tokyo.

Going into the polarized proton-proton run, PHENIX faced the challenge that the RCF would be busy reconstructing and analyzing gold-gold and copper-copper data recorded in 2004 and 2005. The enormous polarized proton-proton data set was transferred to Japan to make use of the substantial computing resources at CCJ, which is comparable to the PHENIX portion of the RCF.

The PHENIX data acquisition can sustain a peak data rate of up to 600 megabytes per second, and runs at a typical rate of 250 megabytes per second while beam is stored in RHIC. The data were buffered at the experimental site before being transferred and archived in the RCF tape library. A 35 terabyte disk-storage system (about 60 hours at typical data rates) allowed PHENIX to archive and transfer data at a lower steady rate, taking advantage of various breaks in the flood of data. A transfer rate of 60 megabytes per second sustained steadily around the clock was able to keep up with the incoming data stream.

Read the full article in this month's CERN Courier

Mesoscale Meteorology and Grid Computing—the L.E.A.D. Project

Globus Consortium Journal

When we discuss grid computing's role in mass-scale data crunching and predictive analysis, many of us associate the discussion with the financial services industry—where Grid powers complex Monte Carlo models to help large brokerages glean new insights into capital markets outcomes/scenarios.

Today, a group of mesocale meteorologists ("mesoscale" referring to the a range from 1–1,000 kilometers) are applying similar Grid principles to making sense of weather patterns—and specifically, predicting and analyzing major weather anomalies (like tornados, hurricanes, earthquakes, etc.).

Predictive analysis and data crunching are certainly not new phenomena for meteorologists—but what we're seeing today is an increasing sophistication in tools at their disposal.