Apache Airavata ApacheCon2013
- 1. c Apache Airavata: Building Gateways to Innova9on Marlon Pierce, Suresh Marru, Saminda Wijeratne, Raminder Singh, Heshan Suriyaarachchi Indiana University
- 2. Thanks to the Airavata PMC • Aleksander Slominski • Lahiru Gunathilake (Incuba4on Mentor) • Marlon Pierce • Amila Jayasekara • Patanachai Tangchaisin • Ate Douma (Incuba4on • Raminder Singh Mentor) • Chathura Herath • Saminda Wijeratne • Chathuri Wimalasena • Shahani Markus • Chris A. Ma<mann Weerawarana (Incuba4on Mentor) • Srinath Perera • Eran Chinthaka • Suresh Marru (Chair) • Heshan Suriyaarachchi • Thilina Gunarathn Apache Airavata became an Apache TLP in September 2012. Thanks also to our incubator champion, Ross Gardler and to Paul Freemantle and Sanjiva Weerawarna for serving as mentors.
- 3. What’s the Point of This Talk? • Don’t let history overly constrain the future. • Broaden awareness of Airavata within the Apache community. • Look for new collabora9ons outside the groups that we normally work with.
- 4. What Is Cyberinfrastructure? “Cyberinfrastructure consists of computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible.” –Craig Stewart, Indiana University See talk by the NSF’s Dr. Dan Katz 2:30 pm during Thursday’s session.
- 6. Science Gateways: Enabling & Democratizing Scientific Research Advanced Science Tools Computational Scientific Algorithms and Archived Data Resources Instruments Models and Metadata Knowledge and Expertise http://sciencegateways.org/
- 7. What Is Apache Airavata? • Science Gateway soRware system to • Compose, manage, execute, and monitor distributed, computa9onal workflows • Wrap legacy command line scien9fic applica9ons with Web services. • Run jobs on computa9onal resources ranging from local resources to computa9onal grids and clouds • Airavata soRware is largely derived from NSF-‐funded academic research.
- 8. Why Do We Care about Apache?
- 9. Two…No, Three Reasons • Open Governance • SoRware should belong to those interested in contribu9ng to it, regardless of funding. • Broadening our developer community • Making be[er connec9ons with Apache. • We couldn’t build Airavata with out the rest of Apache.
- 10. Cyberinfrastructure: How Open is Open Source SoRware? • What’s missing? ü Open source licensing ü Open standards ü Open codes (GitHub, SourceForge, Google Code, etc We also need open governance
- 11. Open Community Software and Governance • Open source projects need diversity, governance. • Reproducibility • Sustainability Compete • Incentives for projects to diversify their developer base. • Govern • Software releases • Contributions • Credit sharing. • Members are added • Project direction decisions. • IP, legal issues Collaborate • Our approach: Apache Software Foundation
- 12. Airavata’s Apache Dependencies Apache Axis2 Workflow Interpreter & WS-messenger services Apache CXF Registry API Front-end implementation Apache OpenJPA, Derby Registry API Back-end implementation Apache Whirr, Hadoop Enabling cloud bursting Apache Shiro, Commons Base for the security framework in Airavata Apache Xmlbeans, Defining serializable descriptors Xmlschema, Axiom Apache Tomcat Hosting the service frameworks
- 13. Some Collabora9on Opportuni9es Apache OODT Workflow Interpreter & WS-messenger services Apache Increase reliability & availability through Casandra data replication Apache Hadoop By introducing capabilities of Hadoop we enable the use of data visualization tools available for hadoop Apache Click, Web base XBaya client, Airavata Flex, Rave, gadgets, Airavata dashboard Shindig
- 14. Science Gateways, Scien9fic Workflows, and Cyberinfrastructure
- 16. Realizing the Universe for the Dark Energy Survey (DES) Using XSEDE Support (Pis: A. Evrard (UM) and A. Kravtsov (UC) • The Dark Energy Survey (DES) is an upcoming interna9onal experiment that aims to constrain the proper9es of dark energy and dark ma[er in the universe using a deep, 5000-‐square degree survey of cosmic structure traced by galaxies. • To support this science, the DES S i m u l a 9 o n W o r k i n g G r o u p i s Fig. 1 The density of dark ma[er in a thin radial slice as seen by a synthe9c observer located in the 8 billion light-‐year computa9onal genera9ng expecta9ons for galaxy volume. Image courtesy Ma[hew Becker, University of Chicago. yields in various cosmologies. • Analysis of these simulated catalogs offers a quality assurance capability for cosmological and astrophysical analysis of upcoming DES telescope data. • T h e s e l a r g e , m u l 9 -‐ s t a g e d computa9ons are a natural fit for w o r k fl o w c o n t r o l a t o p X S E D E resources. Fig. 2: A synthe9c 2x3 arcmin DES sky image showing galaxies, stars, and observa9onal ar9facts. Courtesy Huan Lin, FNAL.
- 17. DES Component Description Application CAMB Code for Anisotropies in the Microwave Background is a serial FORTRAN code that computes the power spectrum of dark matter, which is necessary for generating the simulation initial conditions. Output is a small ASCII file describing the power spectrum. 2LPTic Second-order Lagrangian Perturbation Theory initial conditions code is an MPI based C code that computes the initial conditions for the simulation from parameters and an input power spectrum generated by CAMB. Output is a set of binary files that vary in size from ~80-250 GB depending on the simulation resolution. LGadget LGadget is an MPI based C code that evolves a gravitational N-body system. The outputs of this step are system state snapshot files, as well as lightcone files, and some properties of the matter distribution, including the power spectrum at various timesteps. The total output from LGadget depends on resolution and the number of system snapshots stored, and approaches ~10 TB for large DES simulation boxes.
- 18. DES as a Workflow There are plenty of issues: • Long running code: Based on simulation box size L-gadget can run for 3 to 5 days using more than 1024 cores. • Local HPC provider policies: XSEDE resource provider’s job scheduling policy does not allow jobs to run for more than 24 hours in normal queue • Do-While Construct: Restart service support is needed in workflow. Do-while construct was developed to address the need. • Data size and File transfer challenges: L- gadget produces 10~TB for large DES simulation boxes in system scratch so data need to moved to persistent storage ASAP • File system issues: More than 10,000 lightcone files are doing continues file I/O. This can cause problems with the HPC resource’s file system (usually Lustre-based in XSEDE). Processing steps to build a synthetic galaxy catalog.
- 19. Break for the DES Movie
- 20. Apache Airavata in Ac9on Domain Description Astronomy Image processing pipeline for One Degree Imager instrument on XSEDE Astrophysics Supporting workflow of Dark Energy Survey simulations working group on XSEDE Bioinformatics Supported workflow executions on Amazon EC2 for BioVLAB project Biophysics Manage large scale data analysis of analytical ultracentrifugation experiments on XSEDE and campus resources Computational Manage workflows to support computational Chemistry chemistry parameter studies for ParamChem.org on XSEDE Nuclear Physics Workflows for nuclear structure calculations using Leadership Class Configuration Interaction (LCCI) computations on DOE resources
- 21. Airavata Culture • Java code base • Airavata 0.6 is out, working on 0.7 • What is in a release? • Sprint/scrum + Apache =? • Work through dev mailing list and Jira. • Ac9vely engage students • GSOC • Thanks to Shahani W. • Engage through XSEDE advanced support • Find new usersàcollaborators. • Who belongs on the PMC?
- 23. Apache Airavata L o r ie n m s oi lp e s nu s m Core End Users Developer Message Box Scien4fic Applica4 on Apache Airavata API Applica4on Gateway Developer Workflow Factory Interpreter Computa4onal Resources Regist ry
- 24. Apache Airavata Components Component Description XBaya Workflow graphical composition tool. Registry Service Insert and access application, host machine, workflow, and provenance data. Workflow Interpreter Execute the workflow on one or more resources. Service Application Factory Manages the execution and management of an Service (GFAC) application in a workflow Messaging System WS-Notification and WS-Eventing compliant publish/subscribe messaging system for workflow events Airavata API Single wrapping client to provide higher level programming interfaces.
- 25. Apache Airavata An Architectural introduc9on
- 26. Hi, I’m Nolram. I’m a computa9onal physicist. I run computa9onal experiments everyday This is how typically I run my experiments
- 27. This is star9ng to First I collect my become a very 9ring observed data task And then pass data to my applica9ons & get the result Scien4fic Applica4on Another Scien4fic Applica4on
- 28. How can I make this much simpler…? Logically, this is how my life would be made easier… Is it possible to automate this flow sequence without my guidance?
- 29. The solu9on is to use a workflow-‐powered Scien9sts from many science gateway to different fields face this manage the experiment problem everyday. online. What is a workflow you ask? Well, you just saw one in our previous anima9on…
- 30. We introduce Apache Airavata, a system capable of composing, managing, execu9ng, and monitoring small to large scale applica9ons and workflows Want to see how it works? A Typical Workflow
- 31. … aill hwhile I wait fdata & my I w nd andover my or results, Airavata will complete the experiment wetails (the workflow) Airavata d ill no9fy me with experiment & return me the results progress uhe Airavata y erver to t pdates of m s experiment Results Progress of the experiment Apache Airavata The Gateway
- 32. Let’s look closely how Airavata manages workflows. Experiment progress Apache Airavata Results The Gateway
- 33. Let’s look closely how Airavata manages workflows. Experiment progress Results The Gateway
- 34. 3. Registry Box 4. The MFac 2. G essage 1. Workflow Interpreter Airavata mtain available f tpplica9ons & Defines he has 4 components… Steer s the progress o a he workflow Records cience app execu9ons & data Steer the workflow execu9on records all results of experiments execu9on transfers Message Box GFac Workflow Interpreter The Gateway Registry
- 35. Now you have a basic understanding of what Airavata is, why it is useful & how it works.
- 36. Being a Part of Airavata Community
- 37. Being a Part of Airavata Community Play with different popular Apache technologies & tools Experiment with the Cloud, the Grid… it’s all here… Learn & Engage with a mul9disciplinary community
- 38. The recent impact from the community…
- 39. A Pluggable & Customizable Framework for Registries Apache Airavata Registry API Computa9onal Resources WS Somebody’s App Derby/Casandra
- 40. Support for Cloud- Bursting Applications Apache Airavata Computa9onal Resources
- 41. A Stable API for Airavata Lorem ipsum d insol u ens o p m End Users 1 5 x Scien4fic Applica4on Apache Airavata Gateway Developer Computa9onal Resources
- 42. Solutions for Unique Security Requirements Creden9al Store Apache Airavata Computa9onal Resources
- 43. UNICORE Support Airavata as a Service Real-time Debugging Workflows An Extendable Application Factory The Concept of steering Apps & Workflows
- 44. Impact from Airavata to the community…
- 45. A Generic Applica9on Factory A Pub-‐Sub Messaging Framework Community Creden4al A Creden9al Store Management A Student Introduc9on
- 48. Extend Airavata from your project or extend your project from Airavata
- 49. Or just come up with your own idea to make Airavata better
- 50. Useful Workflow Components Enhanced Data Layer (eg: NoSQL) CLI/Graphical Tools (Plugins,Gadgets,Mobile Apps etc.) Multitenant Support Data Visualization Providers for Computing Resources Throttling Support
- 51. Airavata Easy Deployment • Airavata Deployment Studio (ADS) • FutureGrid • One bu[on configurable deployment o OpenStack, EC2, Eucalyptus o Ubuntu, CentOS, Redhat o X86, 64-‐bit o Airavata 0.6
- 52. ADS Sneak Peak
- 53. ADS Sneak Peak ...
- 54. Further Informa9on • Contact: marpierc@iu.edu, smarru@iu.edu • Apache Airavata: h[p://airavata.apache.org • You can contribute to Apache Airavata! • Join the mailing list: dev@airavata.apache.org • YouTube presenta9on on Apache and NSF Cyberinfrastructure: h[p://www.youtube.com/watch? v=AN7LoQct17U
- 55. References • Images from • h[ps://encrypted-‐tbn2.gsta9c.com • h[p://xmlbeans.apache.org • h[p://airavata.apache.org/ • h[ps://cwiki.apache.org/confluence/display/ AIRAVATA/index