1. 1 E-Research Infrastructure? Markus.Buchhorn@anu.edu.au Head, ANU Internet Futures; Grid Services Coordinator, GrangeNet; Leader, APAC Information Infrastructure Program; (PhD Mt Stromlo 1988-1992)

2. 2 A gentle (and fast!) overview Themes: What does e-Research mean? What kind of infrastructure is involved? How is it being developed?  What are the problems?

3. 3 e-Research + infrastructure The use of IT to enhance research  and education! Access resources transparently Make data readily available Make collaboration easier Is it The Grid ? No, and yes – the Grid is a tool in the kit Who funds it? The Govt – when building for a large community NCRIS (SII+MNRF), ARC, eResearch-CoordC’tee

4. 4 ANU Internet Futures A cross-discipline, cross-campus “applied” research group e-Research infrastructure development Objectives: To investigate and deploy advanced Internet-based technologies that support university research and education missions.  Bring research-edge technologies into production use  Engage with APAC, GrangeNet, ARIIC/SII, …, Internet2, APAN, TERENA, … A strong focus on User Communities  Identify common requirements

5. 5 What does “Grid” mean? Analogy with the power grid A standard service (AC, 240V, 50Hz) A standard connection A standard user interface Users do not care about Various generation schemes Deregulated market  Power auctions Synchronised generators Transmission switching, fail-over systems Accounting and Billing

6. 6 What does “Grid” mean in IT? Transparent use of resources Distributed, and networked Multiple “administrative domains” Other people’s resources become available to you Various IT resources Computing, Data, Visualisation, Collaboration, etc. Hide complexity It should be a “black box”, one just plugs in.

7. 7 What are the bits in eRI? Network Layer (Physical and Transmission) (Advanced) Communications Services Layer Grid, Middleware Services Layer Applications and Users…

8. 8 What’s in that middle bit? Computing Visualisation Collaboration Data Instruments Middle- ware (Advanced) Communications Services Layer Applications and Users…

9. 9 Networks Physical networks are fundamental to link researchers, observational facilities, IT facilities Demand for high-(and flexible) bandwidth to every astronomical site Universities, observatories, other research sites/groups  GrangeNet, AARNet3, AREN, … Big city focus Today remote sites have wet bits of string, and station wagons At least 1-10Gigabit links soon-ish (SSO, ATCA, Parkes, MSO). Getting 10-20Gigabits internationally right now,  including to the top of Mauna Kea in the next year or so Canada, US, NL, … are building/running some 40+Gb/s today e-VLBI, larger detectors, remote control, multi-site collaboration, real-time data analysis/comparisons, … Burst needs, as well as sustained. Wavelength Division Multiplexing (WDM) allows for a lot more bandwidth (80λ at 80Gb/s)

10. 10 Common Needs - Middleware Functionality needed by all the eRI areas Minimise replication of services Provide a standard set of interfaces To applications/users To network layer To grid services Can be built independently of other areas A lot of politics, policy issues enter here

11. 11 Common Needs - Middleware - 2 Authentication Something you have, something you know Somebody vouches for you  Certificate Authorities, Shibboleth, … Authorisation Granularity of permission (resolution, slices, …) Limits of permission (time, cycles, storage, …) Accounting Billing, feedback to authorisation *Collectively called AAA

12. 12 Common Needs - Middleware - 3 Security Encryption, PKI, … AAA, Non-repudiation Firewalls and protocol hurdles (NATs, proxies,…) Resource discovery Finding stuff on the Net  Search engines, portals, registries, p2p mesh, … Capability negotiation  Can you do what I want, when I want Network and application signalling Tell the network what services we need (QoS, RSVP, MPLS, …) Tell the application what the situation is And listen for feedback and deal with it.

13. 13 The Computational Grid Presume Middleware issues are solved… Probably the main Grid activity Architectural Issues  CPUs, endian-ness, executable format, libraries; non-uniform networking; Clusters vs SMP, NUMA, …; Code design  Master/Slave, P2P; Granularity (Fine-grained parallelism vs (coarse) parameter sweep) Scheduling  Multiple owners; Queuing systems; Economics (How to select computational resources, and prioritise) During execution  Job Monitoring and Steering; Access to resources (Code, data, storage, …) But if we solve all these: Seamless access to computing resources across the planet. Harness the power of supercomputers, large->small clusters, and corporate/campus desktops (Campus-Grid)

14. 14 Computing facilities University computing facilities, within departments or centrally. Standout facilities. The APAC partnership (www.apac.edu.au)www.apac.edu.au  Qld: QPSF partnership, several facilities around UQ, GU, QUT  NSW: ac3 (at ATP Everleigh)  ACT: ANU - APAC peak facility, upgraded in 2005 (top 30 in the world)  Vic: VPAC (RMIT)  SA: SAPAC (U.Adelaide?)  WA: IVEC (UWA)  Tas: TPAC (U.Tas) Other very noteworthy facilities, such as Swinburne's impressive clusters. There are bound to be others, and more are planned.

15. 15 Data Grids Large-scale, distributed, “federated” data repositories Making complex data available Scholarly output and scholarly input:  Observations, simulations, algorithms, … to applications and other grid services in the “most efficient” way  Performance, cost, … in the “most appropriate” way  within the same middleware AAA framework in a sustainable and trustworthy way

16. 16 Content Archive Interface Metadata (Ontologies, Semantics, DRM, …) User Queries/Results, Curation ACCESS! and account Computing Visualisation Collaboration Directories: AAA, Capabilities Workflows, DRM,… Rep. Hardware, Software A set of Repositories, sharing a purpose or a theme Data Grid 101 Presentation Authenticate, Authorise

17. 17 Data Grid Issues Every arrow is a protocol, Every interface is a standard Storage: hardware, software; file format standards, algorithms Describing data: metadata, external orthographies, dictionaries Caching/replication: Instances (non-identical), identifiers, derivatives Resource discovery: Harvesting, registries, portals Access: security, rights-management (DRM), anonymity; authsn. granularity Performance: delivery in appropriate form and size, ; user-meaningful user interface (Rendering/presentation – by location and culture) Standards, and the excess thereof Social engineering: Putting data online is  An effort – needs to be easier, obvious  A requirement! – but not enforced; lacks processes  Not recognised nor rewarded PAPER publishing is!

18. 18 Data facilities In most cases these are inside departments, or maybe central services on a university. ANU/APAC host a major storage facility (tape robot) in Canberra that is available for the R&E community to make use of Currently 1.2Petabytes peak, and connected to GrangeNet and AARNet3. It hosts the MSO MACHO-et-al data set at the moment, and more is to come. To be upgraded every 2 years or so – factor of 2-5 in capacity each time  If funding is found, each time. Needs community input. Doesn’t suit everyone (yet) Mirror/collaborating facilities in other cities in AU and overseas being discussed Integration with local facilities VO initiatives – all data from all observatories and computers… Govt initiatives under ARIIC – APSR, ARROW, MAMS, ADT

19. 19 Collaboration and Visualisation A lot of intersection between the two  Beyond videoconferencing - telepresence  Sharing not just your presence, but also your research Examples: Multiple sites of  Large-scale data visualisation, computational steering, engineering and manufacturing design, bio-molecular modelling and visualisation, Education and training  What’s the user interface? Guided tour vs independent observation Capability negotiation, local or remote rendering (Arbitrary) application sharing Tele-collaboration (Co-laboratories)  Revolve around the Access Grid www.accessgrid.org

20. 20 Access Grid “Nodes” A collection of interactive, multimedia centres that support collaborative work distributed large-scale meetings, sessions, seminars, lectures, tutorials and training. High-end, large-scale “tele-collaboration” facilities Or can run on a single laptop/PDA Videoconferencing dramatically improved But not the price Much better support for  multi-site, multi-camera, multi-application interaction Flexible, open design Over 400 in operation around the world 30+ in operation, design or construction in Australia 4+ at ANU

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22. 22 AccessGrid facilities University hosted nodes are generally available for researchers from any area to use, you just need to make friends with their hosts. Qld: JCU-Townsville, CQU-several cities, UQ, QUT, CQU, SQU, GU (Nathan, GoldCoast) NSW: USyd, UNSW(desktop), UTS ACT: ANU (4+, one at Mt Stromlo. SSO has been suggested) Vic: UMelb (soon), Monash-Caulfield, VPAC (by RMIT), Swinburne (desktop), U.Ballarat (desktop) SA: U.Adelaide (1 desktop and 1 room), Flinders (soon), UniSA (planning) WA: UWA (IVEC) Tas: UTas (soon) NT: I wish! Another 400+ around the world. Development by many groups, Australia has some leadership Accessgrid-l@grangenet.net

23. 23 Visualisation Facilities Active visualisation research community in Australia  OzViz'04 at QUT 6-7 Dec 2004. Major nodes with hard facilities include  ANU-VizLab,  Sydney-VisLab,  UQ/QPSF-VisLab,  IVEC-WA,  I-cubed (RMIT),  Swinburne,  etc.

24. 24 Online Instruments Remote, collaborative access to unique / scarce instruments: Telescopes, Microscopes, Particle accelerators, Robots, Sensor arrays Need to interface with other eRI services Computation – analysis of data Data – for storage, comparison Visualisation – for human analysis Collaboration – to share the facility

25. 25 So, in summary: Transparent use of various IT resources Research and education processes Make existing ones easier and better Allow new processes to be developed Are we there yet? Not even close!! But development in many areas is promising In some situations, the problems are not technical but political/social Some of the results already are very useful Astronomy needs to help the processes, to help Astronomy!