GRID COMPUTING &IT’S APPLICATIONS / LHC GRID

Alokeparna ChoudhuryStream. CSERoll No. 20091005Reg. No. 2783 of 2009-10University Institute of Technology

INTRODUCTION TO GRID COMPUTING

WHAT IS GRID?

In Grid computing the word “GRID” comes from the concept “Grating of crisscrossed parallel bars”

Grid is a network of horizontal and perpendicular lines, uniformly spaced by means of a system of coordinates.

In grid computing the computing data and resources are implementing in a GRID network.

WHY DO WE NEED GRIDS?

Many large-scale problems cannot be solved by a single computer

Globally distributed data and resources

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GRID ARCHITECHTURE

CONTD. The architecture for grid computing systems consists of four layers. The lowest fabric layer provides interfaces to local resources at a

specific site. The connectivity layer consists of communication protocols for

supporting grid transactions. In addition the connectivity layer will contain security protocols to

authenticate users and resources. The resource layer is responsible for managing a single resource. The collective layer deals with handling access to multiple

resources. It typically consists of services for resource discovery, allocation

and scheduling of tasks onto multiple resources. Finally , the application layer consists of the applications that

operate within a virtual organization and which make use of the grid computing environment.

FROM GRIDS TO CLOUD COMPUTING• Logical steps:– Make the grids public– Provide much simpler interfaces (and more limited

control)– Charge usage of resources

However, the promise of cloud computing finds a great user base in science grids due to:– Intense computations– Huge amounts of storage needs

CONTD. Much of the Grid research community is now working on

clouds.

It is quite feasible to have a cloud within a computational grid, as it is possible to have a computational grid as a part of a cloud.

In a computational grid, one large job is divided into many small portions and executed on multiple machines. This characteristics is fundamental to a grid, not so in a cloud.

SOME GRID APPLICATIONS

Distributed supercomputing High-throughput computing On-demand computing Data-intensive computing Collaborative computing

INTRODUCTION TO LCG

The LHC Computing Grid(LCG) was approved by the CERN council on 20th September 2001 to develop, build and maintain a distributed computing infrastructure for the storage & analysis of data from the 4 LHC experiments.

The project was defined with 2 distinct phases.

In Phase 1(2002-2005) the required s/w & services would be developed & prototyped.

In Phase2(2006-2008) the initial services for the 1st beams from the LHC machine would be constructed & brought into operation.

WLCG Worldwide LHC Computing Grid

--Distributed Computing Infrastructure for LHC experiments Linking 3 distributed infrastructures

-OSG Open Science Grid in the US

-EGI European Grid Infrastructure

-NDGF Nordic Data Grid Facility Linking more than 300 computer centers Providing > 340,000 cores To more than 2000(active) users Moving ~10GB/s for each experiment Archiving 15PB per year

THE LHC WITH GRID COMPUTING

The Large Hadrons Collider(LHC), starting to operate in 2007, will produce roughly 15 Pet bytes(15 million GB) of data annually.

The mission of the LHC Computing Grid (LCG) project is to build & maintain a data storage and analysis infrastructure for the entire high energy physics community that will use the LHC.

CONTD.

In the case of the LHC , a novel globally distributed model for data storage and analysis-a computing grid-was chosen to centralize all of this capacity at one location near the experiments.

The LCG Project will implement a grid to support the computing models of the experiments using a distributed four-tiered model.

TIER-0

The original raw data emerging from the data acquisition systems will be recorded at the Tier-0 centre at CERN.

The maximum aggregate bandwidth for raw data recording for a single experiment(ALICE) is 1.25GB/s.

ALICE is A Large Ion Collider Experiment and is prepared for CERN’s Large Hadrons collider. It concerns with the Grid Computing technologies, needed to analyze ALICE data.

CONTD. The first-pass reconstruction will take place at the Tier-0,

where a copy of the reconstructed data will be stored.

The tier-0 will distribute a second copy of the raw data across the Tier-1 centre associated with the experiment.

Additional copies of the reconstructed data will also be distributed across the Tier-1 centre according to the policies of each experiment.

TIER-1

The role of the Tier-1 center varies according to the experiment, but in general they have the prime responsibility for managing the permanent data storage-raw, simulated and processed data.

It provides computational capacity for reprocessing and for analysis process that require access to large amounts of data.

At present 11 Tier-1 centers have been defined, most of them serving several experiments.

TIER-2

The role of the Tier-2 centers is to provide computational capacity and appropriate storage services for Monte Carlo event simulation and for end user analysis.

The Tier-2 centers will obtain data as required from Tier-1 centers, and the data generated at Tier-2 will be sent to Tier-1 for permanent storage.

More than 100 Tier-2 centers have been identified.

TIER-3

Other computing facilities in universities and laboratories will take part in the processing and analysis of LHC data as Tier-3 facilities.

These lie outside the scope of the LCG project, although they must be provided with access to the data and analysis facilities as decided by the experiments.

As part of WLCG there are 2 “Tier-2” sites in India: TIFR in Mumbai and VECC in Kolkata

KOLKATA TIER-2

SUMMARY Grid Computing and WLCG has proven itself during the first

year of data-taking of LHC. Grid Computing works for WLCG community and has a

future. Long term sustainability will be a challenge.

FUTURE Stable WANs will provide excellent performance and move to

a less hierarchical model. Virtualization and cloud computing. Moving towards standards. Integrating new technology.

REFERENCESREFERENCES https://openlab-mu-internal.web.cern.ch cg-

archive.web.cern.ch/lcg.../lhcgridfest/.../Robertson_Les_GridFest.pdf

scientific-journals.org/journalofsystemsandsoftware/.../vol2no5_4.pdf

edutechwiki.unige.ch/en/Grid_computing www.redbooks.ibm.com/redbooks/pdfs/sg246778.

pdf Distributed Systems-principles and paradigms-

Andrew S. Tanenbaum , Maarten Van Steen