The National e-Science Centre

and UK e-Science Programme

The National e-Science Centre

and UK e-Science Programme

Muffy Calder

University of Glasgow

http: //www.nesc.ac.ukhttp://www.dcs.gla.ac.uk/~muffy

Muffy Calder

University of Glasgow

http: //www.nesc.ac.ukhttp://www.dcs.gla.ac.uk/~muffy

An overviewAn overview

• E-Science– challenges and opportunities

• Grid computing – challenges and opportunities

• Activities– UK and international– Scotland and National e-Science Centre

• E-Science– challenges and opportunities

• Grid computing – challenges and opportunities

• Activities– UK and international– Scotland and National e-Science Centre

e-Sciencee-Science

‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’

‘e-Science will change the dynamic of the way science is undertaken.’

John Taylor

Director General of Research Councils

Office of Science and Technology

‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’

‘e-Science will change the dynamic of the way science is undertaken.’

John Taylor

Director General of Research Councils

Office of Science and Technology

The drivers for e-ScienceThe drivers for e-Science

• More data– instrument resolution and laboratory automation– storage capacity and data sources

• More computation– computations available, simulations doubling every year

• Faster networks– bandwidth– need to schedule

• More interplay and collaboration– between scientists, engineers, computer scientists etc.– between computation and data

• More data– instrument resolution and laboratory automation– storage capacity and data sources

• More computation– computations available, simulations doubling every year

• Faster networks– bandwidth– need to schedule

• More interplay and collaboration– between scientists, engineers, computer scientists etc.– between computation and data

The drivers for e-ScienceThe drivers for e-Science

• Exploration of data and models – in silico discovery

• Floods of public data– gene sequence doubling every 9 months– Searches required doubling every 4-5 months

In summary

Shared data, information and computation by geographically dispersed communities.

• Exploration of data and models – in silico discovery

• Floods of public data– gene sequence doubling every 9 months– Searches required doubling every 4-5 months

In summary

Shared data, information and computation by geographically dispersed communities.

Current model: ad-hoc client-serverCurrent model: ad-hoc client-server

HPC

HPCAnalysis

Storage

Storage

Analysis

Experiment

ExperimentComputing

HPC

Scientist

The vision: computation & information utilityThe vision: computation & information utility

MIDLEWARE

Experiment

Experiment

Computing

Computing

Computing

Storage

Storage

Storage

Analysis

Analysis

Scientist

e-Science Examples e-Science Examples

• Bioinformatics/Functional genomics• Collaborative Engineering• Medical/Healthcare informatics• Earth Observation Systems (flood monitoring)• TeleMicroscopy• Virtual Observatories• Robotic Telescopes• Particle Physics at the LHC

– EU DataGrid particle physics, biology & medical imaging, Earth observation

– GridPP, ScotGrid

– AstroGrid

• Bioinformatics/Functional genomics• Collaborative Engineering• Medical/Healthcare informatics• Earth Observation Systems (flood monitoring)• TeleMicroscopy• Virtual Observatories• Robotic Telescopes• Particle Physics at the LHC

– EU DataGrid particle physics, biology & medical imaging, Earth observation

– GridPP, ScotGrid

– AstroGrid

•Lift Capabilities•Drag Capabilities•Responsiveness

•Deflection capabilities•Responsiveness

•Thrust performance•Reverse Thrust performance•Responsiveness•Fuel Consumption

•Braking performance•Steering capabilities•Traction•Dampening capabilities

Crew Capabilities- accuracy- perception- stamina- re-action times- SOP’s Engine Models

Airframe Models

Wing Models

Landing Gear Models

Stabilizer Models

Human Models

Multi-disciplinary Simulations Multi-disciplinary Simulations

Whole system simulations are produced by couplingall of the sub-system simulations

Multi-disciplinary Simulations Multi-disciplinary Simulations

VirtualNational Air

SpaceVNAS

GRCEngine Models

LaRC

Airframe Models

LandingGear Models

ARC

Wing Models

Stabilizer Models

Human Models

•FAA Ops Data•Weather Data•Airline Schedule Data•Digital Flight Data•Radar Tracks•Terrain Data•Surface Data

22,000 CommercialUS Flights a day

50,000 Engine Runs

22,000 Airframe Impact Runs

132,000 Landing/Take-off

Gear Runs

48,000 Human Crew Runs

66,000 Stabilizer Runs

44,000 Wing Runs

SimulationDrivers

(Being pulled togetherunder the NASA AvSPAviation ExtraNet (AEN)

Many aircraft, flight paths, airport operations, and the environment are combined to get a virtual national airspace

US National Air Space Simulation Environment

Global in-flight engine diagnosticsGlobal in-flight engine diagnostics

in-flight data

airline

maintenance centre

ground station

global networkeg SITA

internet, e-mail, pager

DS&S Engine Health Center

data centre

Distributed Aircraft Maintenance Environment: Universities of Leeds, Oxford, Sheffield &York

LHC computingLHC computing

Tier2 Centre ~1000 PCs

Online System

Offline Farm~20,000 PCs

CERN Computer Centre >20,000 PCs

RAL Regional Centre

US Regional Centre

French Regional Centre

Italian Regional Centre

InstituteInstituteInstituteInstitute ~200 PCs

Workstations

~100 MByte/sec

~100 MByte/sec

100 - 1000 Mbit/sec

•one bunch crossing per 25 ns

•100 triggers per second

•each event is ~1 MByte

physicists work on analysis “channels”

each institute has ~10 physicists working on one or more channels

data for these channels is cached by the institute server

Physics data cache

~PByte/sec

~ Gbit/sec or Air Freight

Tier2 Centre ~1000 PCs

Tier2 Centre ~1000 PCs

~Gbit/sec

Tier 0Tier 0

Tier 1Tier 1

Tier 3Tier 3

Tier 4Tier 4

assumes PC = ~ 25 SpecInt95

ScotGRID++ ~1000 PCs

Tier 2Tier 2

Emergency response teamsEmergency response teams

• bring sensors, data, simulations and experts together– wildfire: predict movement of fire &

direct fire-fighters

– also earthquakes, peacekeeping forces, battlefields,…

• bring sensors, data, simulations and experts together– wildfire: predict movement of fire &

direct fire-fighters

– also earthquakes, peacekeeping forces, battlefields,…

Los Alamos National Laboratory: wildfireNational Earthquake Simulation Grid

Earth observationEarth observation

• ENVISAT– € 3.5 billion– 400 terabytes/year– 700 users

• ENVISAT– € 3.5 billion– 400 terabytes/year– 700 users

• ground deformation prior to a volcano

• ground deformation prior to a volcano

To achieve e-Science we need…To achieve e-Science we need…

To achieve e-Science we need…To achieve e-Science we need…

Grid the visionGrid the vision

Computing resources

Data

Knowledge

Instruments

PeopleSolution

Complex problem

GRID

The GridThe Grid

• Computing cycles, data storage, bandwidth and facilities viewed as commodities.– like the electricity grid

• Software and hardware infrastructure to support model of computation and information utilities on demand.– middleware

• An emergent infrastructure – delivering dependable, pervasive and uniform access to a set of

globally distributed, dynamic and heterogeneous resources.

• Computing cycles, data storage, bandwidth and facilities viewed as commodities.– like the electricity grid

• Software and hardware infrastructure to support model of computation and information utilities on demand.– middleware

• An emergent infrastructure – delivering dependable, pervasive and uniform access to a set of

globally distributed, dynamic and heterogeneous resources.

The GridThe GridSupporting computations with differing characteristics:

• Highthroughput– Unbounded, robust, scalable, use otherwise idle machines

• On demand– short-term bounded, hard timing constraints

• Data intensive– computed, measured, stored, recalled, e.g. particle physics

• Distributed supercomputing– classical CPU and memory intensive

• Collaborative– mainly in support of hhi, e.g. access grid

Supporting computations with differing characteristics:

• Highthroughput– Unbounded, robust, scalable, use otherwise idle machines

• On demand– short-term bounded, hard timing constraints

• Data intensive– computed, measured, stored, recalled, e.g. particle physics

• Distributed supercomputing– classical CPU and memory intensive

• Collaborative– mainly in support of hhi, e.g. access grid

Grid DataGrid Data

• Generated by sensor

• From a database

• Computed on request

• Measured on request

• Generated by sensor

• From a database

• Computed on request

• Measured on request

Grid ServicesGrid Services• Deliver bandwidth, data, computation cycles

• Architecture and basic services for– authentication– authorisation– resource scheduling and coscheduling– monitoring, accounting and payment– protection and security– quality of service guarantees– secondary storage– directories– interoperability – fault-tolerance– reliability

• Deliver bandwidth, data, computation cycles

• Architecture and basic services for– authentication– authorisation– resource scheduling and coscheduling– monitoring, accounting and payment– protection and security– quality of service guarantees– secondary storage– directories– interoperability – fault-tolerance– reliability

But…has the emperor got any clothes on?But…has the emperor got any clothes on?

• Maybe string vest and pants:

– semantic web • machine understandable information on the web

– virtual organisations

– pervasive computing

“ … a billion people interacting with a million e-businesses with a trillion

intelligent devices interconnected ” Lou Gerstner, IBM (2000)

• Maybe string vest and pants:

– semantic web • machine understandable information on the web

– virtual organisations

– pervasive computing

“ … a billion people interacting with a million e-businesses with a trillion

intelligent devices interconnected ” Lou Gerstner, IBM (2000)

National and International ActivitiesNational and International Activities• USA

– NASA Information Power Grid– DOE Science Grid– NSF National Virtual Observatory etc.

• UK e-Science Programme• Japan – Grid Data Farm, ITBL• Netherlands – VLAM, PolderGrid• Germany – UNICORE, Grid proposal• France – Grid funding approved• Italy – INFN Grid• Eire – Grid proposals• Switzerland - Network/Grid proposal• Hungary – DemoGrid, Grid proposal• …

• USA– NASA Information Power Grid– DOE Science Grid– NSF National Virtual Observatory etc.

• UK e-Science Programme• Japan – Grid Data Farm, ITBL• Netherlands – VLAM, PolderGrid• Germany – UNICORE, Grid proposal• France – Grid funding approved• Italy – INFN Grid• Eire – Grid proposals• Switzerland - Network/Grid proposal• Hungary – DemoGrid, Grid proposal• …

Cambridge

Newcastle

Edinburgh

Oxford

Glasgow

Manchester

Cardiff

Soton

London

Belfast

DL

RAL Hinxton

UK e-science centres

AccessGrid always-on video walls

AccessGrid always-on video walls

National e-Science CentreNational e-Science Centre• Edinburgh + Glasgow Universities

– Physics & Astronomy 2– Informatics, Computing Science– EPCC

• £6M EPSRC/DTI + £2M SHEFC over 3 years

• Edinburgh + Glasgow Universities– Physics & Astronomy 2– Informatics, Computing Science– EPCC

• £6M EPSRC/DTI + £2M SHEFC over 3 years

• e-Science Institute– visitors, workshops, co-ordination, outreach

• middleware development– 50 : 50 industry : academia

• UK representation at GGF• coordinate regional centres

• e-Science Institute– visitors, workshops, co-ordination, outreach

• middleware development– 50 : 50 industry : academia

• UK representation at GGF• coordinate regional centres

Generic Grid MiddlewareGeneric Grid Middleware

• All e-Science Centres will donate resources to form a UK ‘national’ Grid

• All Centres will run same Grid Software- based on Globus*, SRB and Condor

• Work with Global Grid Forum (GGF) and major computing companies.

*Globus – project to develop open architecture, open source Grid software, Globus toolkit 2.0 now available.

• All e-Science Centres will donate resources to form a UK ‘national’ Grid

• All Centres will run same Grid Software- based on Globus*, SRB and Condor

• Work with Global Grid Forum (GGF) and major computing companies.

*Globus – project to develop open architecture, open source Grid software, Globus toolkit 2.0 now available.

How can you participate?How can you participate?

• Informal collaborations

• Formal collaborative LINK funded projects

• Attend seminars at eSI

• Suggest visitors for eSI

• Suggest themes and topics for eSI.

• Informal collaborations

• Formal collaborative LINK funded projects

• Attend seminars at eSI

• Suggest visitors for eSI

• Suggest themes and topics for eSI.

eSI forthcoming eventseSI forthcoming events

Friday, March 15 Blue Gene Monday, March 18 IWOX: Introductory Workshop on XML Schema

Tuesday, March 19 AWOX: Advanced Workshop on XML: XML Schema, Web Services and Tools

Thursday, March 21 GOGO: Getting OGSA Going 1

Monday, April 8 Software Management for Grid Projects

Monday, April 15 DAI: Database Access and Integration

Wednesday, April 17 DBFT Meeting

Monday, April 29 The Information GridSunday, July 21 GGF5/ HPDC11

Friday, March 15 Blue Gene Monday, March 18 IWOX: Introductory Workshop on XML Schema

Tuesday, March 19 AWOX: Advanced Workshop on XML: XML Schema, Web Services and Tools

Thursday, March 21 GOGO: Getting OGSA Going 1

Monday, April 8 Software Management for Grid Projects

Monday, April 15 DAI: Database Access and Integration

Wednesday, April 17 DBFT Meeting

Monday, April 29 The Information GridSunday, July 21 GGF5/ HPDC11

Watch the web pages…. www.nesc.ac.uk

Thank you!

Watch the web pages…. www.nesc.ac.uk

Thank you!