International Grid Communities

Dr. Carl Kesselmancarl@isi.edu

Information Sciences InstituteUniversity of Southern California

The Grid Problem

Resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations

Enabling International Cooperation International cooperation valuable, because

– Scale of Grid problem is large– Expertise on both sides of Atlantic & Pacific– Important international applications– Cost of noncooperation can be high

Useful cooperation will not just happen but must be explicitly encouraged– Substantial testbed & application projects, jointly

sponsored by EU, US, others– Transatlantic ‘Terabit’ Testbed, etc.– International Virtual Data Grid Laboratory

Grid Forum

IETF like body to codify standard practice Two meetings held so far, next in April European Grid forum established to

address Europe specific issues

Layered Grid Architecture(By Analogy to Internet Architecture)

Application

Fabric“Controlling things locally”: Access to, & control of, resources

Connectivity“Talking to things”: communication (Internet protocols) & security

Resource“Sharing single resources”: negotiating access, controlling use

Collective“Coordinating multiple resources”: ubiquitous infrastructure services, app-specific distributed services

InternetTransport

Application

Link

Inte

rnet P

roto

col

Arch

itectu

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The Grid Physics Network

Petabyte-scale computational environment for data intensive science– CMS and Atlas Projects of the Large

Hadron Collider– Laser Interferometer Gravitational-

Wave Observatory– Sloan Digital Sky Survey (200 million

objects each with ~100 attributes)

Data Grids

Integrate data archives into a distributed data management and analysis “Grid”

More than storage & network, also e.g.– Caching and mirroring to exploit locality

– Intelligent scheduling to determine appropriate replica, site for (re)computation, etc.

– Coordinated resource management for performance guarantees

– Embedded security, policy, agent technologies for effective distributed analysis

Virtual Data Grids Only raw data must exist

– Dynamic data production Large extent and scale

– national or worldwide, multiple distance scales

– large numbers of resources Sophisticated new services

– Coordinated use of remote resources Transparency in data-handling and processing

– Optimize for cost, time, policy constraints, …

Grid Communities & Applications:Data Grids for High Energy Physics

Tier2 Centre ~1 TIPS

Online System

Offline Processor Farm

~20 TIPS

CERN Computer Centre

FermiLab ~4 TIPSFrance Regional Centre

Italy Regional Centre

Germany Regional Centre

InstituteInstituteInstituteInstitute ~0.25TIPS

Physicist workstations

~100 MBytes/sec

~100 MBytes/sec

~622 Mbits/sec

~1 MBytes/sec

There is a “bunch crossing” every 25 nsecs.

There are 100 “triggers” per second

Each triggered event is ~1 MByte in size

Physicists work on analysis “channels”.

Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server

Physics data cache

~PBytes/sec

~622 Mbits/sec or Air Freight (deprecated)

Tier2 Centre ~1 TIPS

Tier2 Centre ~1 TIPS

Tier2 Centre ~1 TIPS

Caltech ~1 TIPS

~622 Mbits/sec

Tier 0Tier 0

Tier 1Tier 1

Tier 2Tier 2

Tier 4Tier 4

1 TIPS is approximately 25,000

SpecInt95 equivalents

Image courtesy Harvey Newman, Caltech

Virtual Data ToolsRequest Planning and Scheduling

Tools

Request Execution Management

Tools

Transforms

Distributed resources(code, storage,computers, and network)

Resource Management

Services

Resource Management

Services

Security and Policy Services

Security and Policy Services

Other Grid

Services

Other Grid

Services

Interactive User Tools

Production Team

Individual Investigator Other Users

Raw data source

GriPhyn Architecture

?

Major Archive Facilities

Network caches & regional centers

Local sites

GriPhyn Usage Scenario

iVDGL International Virtual-Data Grid Laboratory

– A place to conduct Data Grid tests at scale

– Concrete manifestation of world-wide grid activity

– Continuing activity that will drive Grid awareness

– A basis for further funding Scale of effort

– For national, intl scale Data Grid tests, operations

– Computationally and data intensive computing

– Fast networks Who

– Initially US-UK-EU; Japan, Australia

– Other world regions later

– Discussions w/ Russia, China, Pakistan, India, South America

Structure of the iVDGL

Grid Operations Center Virtual-Data Grid Infrastructure (common middleware and services)

International Experiments

Education and Outreach

Grid Technology Development DataGrid Laboratory Users

DataGrid Laboratory

Resource Providers Resource Centers (Storage and Compute)

Experiment Resources (Storage and Compute)

Outreach Centers (Storage and Compute)

Compute Platform Storage Platform

iVDGL Monitoring Interface

iVDGL Mgmt. Interface

iVDGL Control Interface

Local Management Interface Interface

iGLS

Experiment Scheduler

Health and Status Monitoring

iVDGL Configuration Information

Access Control and Policy Services

iGOCExperiment

Management

Experiment Data Collection

Application Experiments

iVDGL Architecture

iVDGL Map Circa 2003-2004

Tier0/1 facility

Tier2 facility

10 Gbps link

2.5 Gbps link

622 Mbps link

Other link

Tier3 facility

iVDGL as a Laboratory Grid Exercises

– “Easy”, intra-experiment tests first (10-20%, national, transatlantic)

– “Harder” wide-scale tests later (50-100% of all resources)

Local control of resources vitally important– Experiments, politics demand it

Strong interest from other disciplines– HEP + NP experiments

– Virtual Observatory (VO) community in Europe/US

– Gravity wave community in Europe/US/(Japan?)

– Earthquake engineering

– Bioinformatics

– Computer scientists (wide scale tests)

Conclusions

Application communities for major Grid experiments are international– More communities then those mentioned

International testbeds are coming Wires are only part of the solution Common middleware archecture enabling

technology