1. Grid Rapid Application Virtualization Interface (gRAVI) - Service Oriented Science Ravi K Madduri, Argonne National Laboratory/ University of Chicago Joshua Boverhof, Lawrence Berkeley Laboratory Kyle Chard, University of Wellington, NZ Dinanath Sulakhe, University of Chicago Cem Onyukusel, CMU Ian Foster, University of Chicago/ANL

2. Agenda l What is Service Oriented Science ? u Software as a service u Examples from industry (google, salesforce.com etc) u Examples of SoS from Scientific communities l Why are we excited about this ? u How this helps Science l Sum of parts greater u Sustainable infrastructure u Virtualization l Different aspects of SoS u Authoring u Deploying and Securing u Discovery u Provisioning on demand u Composition l How does it help you ? u End users perspective – Brian’s talk u Bio workflow l Conclusions and Further resources u Q & A

3. Examples of SaaS from Industry l Salesforce.com l Google Calendar, Google docs, Google spell check etc.. l Amazon S3, EC2 l Flickr l Facebook l Microsoft Live l And on and on….

4. Service-Oriented Science l People create services (data or functions) … l which I discover (& decide whether to use) … l & compose to create a new function... l & then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

5. Creating Services People create services (data, code, instr.) … which I discover (& decide whether to use) … & compose to create a new function... & then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

6. Creating Services Introduce + gRAVI Shannon Hastings Scott Oster David Ervin Stephen Langella Joshua Boverhof Kyle Chard Ravi Madduri

7. Introduce Overview l A framework which enables fast and easy creation of Globus based grid services l Provide easy to use graphical service authoring tool. l Hide all “grid-ness” from the developer l Utilize best practice layered grid service architecture l Integration with other core grid services and architecture components u GAARDS Security Infrastructure (Dorian, GridGrouper, CSM) u Globus Index Service u Global Model Exchange (GME) u Cancer Data Standards Repository l Extension Framework for integrating with other architecture components

8. Inside the Introduce created service l Services have many moving and configurable parts which support features such as: u Advertisement u Discovery u Invocation u Security (Authentication/Authorization) u Stateful Resources l The Introduce Toolkit can keep all these features in sync as the developer creates and modifies the grid service

9. Introduce Features l Supports modification of operations u Adding operations u Removing Operations u Updating Operations u Importing Operations l Graphical Configuration u Advertisement u Security u Service Metadata Specification u Service Metadata Editing u Service Configuration Properties l Auto Generates Code for Service l Auto generates a client API for service. l Graphical Deployment of Service u Globus u Tomcat u JBoss

10. Appln Service Create Index service Store Repository Service Advertize Discover Invoke; get results Introduce Container Transfer GAR Deploy gRAVI l Grid Remote Application Virtualization Interface l Builds on Introduce u Define service u Create skeleton u Discover types u Add operations u Configure security l Wrap arbitrary executables

11. Discovering Services People create services (data or functions) … which I discover (& decide whether to use) … & compose to create a new function... & then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

12. Discovering Services WS-MDS+ Taverna Laura Pearlman Mike Darcy myGrid Team

13.  The ultimate arbiter?  Types, ontologies  Can I use it?  Billions of services Discovering Services Assume success Semantics Permissions Reputation A B

14. Discovery (1): Registries Globus

15. Composing Services People create services (data or functions) … which I discover (& decide whether to use) … & compose to create a new function... & then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

16. Taverna caGrid Scavenger with semantic/metadata based caGrid service query A sample caGrid workflow

17. Hosting Services People create services (data or functions) … which I discover (& decide whether to use) … & compose to create a new function... & then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

18. Provisioning Services WS-GRAM + VWS Martin Feller Stuart Martin Kate Keahey Tim Freeman Joshua Boverhof

19. Provisioning using WS-GRAM l gRAVI uses JSDL for Application Description l Generates a method on the generated service called GRAM l Generates implementation that creates a GramJob from Application Description l Uses the bootstrapped community credential to run the application as a grid job l Used widely in realizing the usecases from caBIG community

20. Repository Service Using VWS/Cloud Computing l gRAVI service u Wrap the application as Service u Create the GAR and put in repository l Provision resources u Use clouds (VMM) l start service u Transfer gar, deploy l Index Service u Grid service registers itself nimbusstratus Index service Transfer, deploy Register service Create VM provision discovery portal GAR

21. Cloud Computing

22. SoS Deployments

23. cancer Biomedical Informatics Grid (caBIG™) l A national, NCI-funded program with participants from cancer centers and research institutions u Improve cancer research and accelerate efforts to find a cure for cancer u Make cancer research data and tools (maintained at different sites) more efficiently accessible to researchers u Create scalable, federated, actively managed biomedical informatics network that will connect members of the cancer research enterprise u Informatics support for basic, clinical, and translational research u “National Standards, Local Management” * l caBIG community u 50+ Cancer Centers, 30+ Organizations, over 900 participants

24. Example Scenario Location A Microarray, Protein, Image data Location B Microarray, Protein, Image data Location C Microarray, Protein, Image data Location C Image Analysis Location D Image Analysis Microarray and protein databases at other institutions caGrid Service Interfaces caGrid Environment Registered Object Definitions Advertisement Log on, Grid credentials Query and Analysis Workflow Discovery

25. Users Experience l Early Adopters u Love it ! u 45 services from 50+ cancer centers (and growing) l Some services are lot more popular than others l Bio-informatics group at Argonne – Details in subsequent slides u APS plans to pursue this model – Brian Tieman will talk more about this l End users u caBIG hack-a-thon participants were happy about workflows u Cancer Centers l Not too happy right now l Would like to see some RoI

26. Integration of caBIG-geWorkbench-Teragrid

27. caGrid Security (GTS, Grid Grouper, Dorian, CDS) http://www.cagrid.org/mwiki/index. php?title=GAARDS:Main

28. Transposon Workflow Details l Transposons are small mutant sequences of DNA that move between positions within the genome of a cell l Gene functions can be identified by inserting mutant sequences into a genome and analysing where the sequence resides (between genes or on a gene) and how it affects its phenotype l BLAST is used to compare the genome after insertion against the original genome u This identifies where the transposon resides

29. Realizing the workflow Format DB BLAST Create Report Create a fasta file representing the Genome sequences Compare these sequences against the original genome Find Transposo n Find sequences that have the given transposon Neighbouring Genes Neighbouring Genes BLAST Misses BLAST Misses BLAST Hits BLAST Hits Compile a report summarising where the transposon was inserted and results of the BLAST search Loop Until there are no misses or all genomes have been searched Genome Sequences

31. Center for Enabling Distributed Petascale Science Workflow Automation at DOE Facilities Automation Reproducibility Security Reusability Storage Metadata Analysis Visualization Advanced Photon Source

32. Lessons Learned l Nice higher level abstraction u Suitable for a subset of scientific computing usecases l Sustainable infrastructure l Work well with hospital/cancer center/APS IT infrastructure l Workflows l Scalability l Provenance l No Vendor lock-in (if you are careful)

33. Further Resources l Further Details on gRAVI u http://dev.globus.org/wiki/Incubator/gRAVI http://dev.globus.org/wiki/Incubator/gRAVI l Further Details on Introduce u www.cagrid.org www.cagrid.org l Details on Taverna + gRAVI u http://dev.globus.org/wiki/Using_gRAVI_Se rvices_in_Taverna http://dev.globus.org/wiki/Using_gRAVI_Se rvices_in_Taverna l gRAVI users mailing list u gravi-users@globus.org