6th Biennial Ptolemy Miniconference Berkeley, CA May 12, 2005 Distributed Computing in Kepler Ilkay Altintas Lead, Scientific Workflow Automation Technologies.

Slides:



Advertisements
Similar presentations
Nimrod/K: Towards Massively Parallel Dynamic Grid Workflows David Abramson, Colin Enticott, Monash Ilkay Altinas, UCSD.
Advertisements

1 Flexible IO Services in the Kepler Grid Workflow System David Abramson Jagan Kommineni Ilkay Altintas
LEAD Portal: a TeraGrid Gateway and Application Service Architecture Marcus Christie and Suresh Marru Indiana University LEAD Project (
Abstraction Layers Why do we need them? –Protection against change Where in the hourglass do we put them? –Computer Scientist perspective Expose low-level.
A Workflow Engine with Multi-Level Parallelism Supports Qifeng Huang and Yan Huang School of Computer Science Cardiff University
5/30/2012. Provides a method for finding services/data on the Exchange Network – discover data. Supports User Friendly Tools Can automatically collect.
GENI Experiment Control Using Gush Jeannie Albrecht and Amin Vahdat Williams College and UC San Diego.
Data Grid: Storage Resource Broker Mike Smorul. SRB Overview Developed at San Diego Supercomputing Center. Provides the abstraction mechanisms needed.
UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Scientific Workflow Automation Technologies Provenance Collection Support in the Kepler Scientific Workflow.
High Performance Computing Course Notes Grid Computing.
Jianwu Wang, Daniel Crawl, Ilkay Altintas San Diego Supercomputer Center, University of California, San Diego 9500 Gilman Drive, MC 0505 La Jolla, CA ,
Condor-G: A Computation Management Agent for Multi-Institutional Grids James Frey, Todd Tannenbaum, Miron Livny, Ian Foster, Steven Tuecke Reporter: Fu-Jiun.
The EPIKH Project (Exchange Programme to advance e-Infrastructure Know-How) gLite Grid Services Abderrahman El Kharrim
1 Software & Grid Middleware for Tier 2 Centers Rob Gardner Indiana University DOE/NSF Review of U.S. ATLAS and CMS Computing Projects Brookhaven National.
RBAC and JXTA 1 Role Based Access Control and the JXTA P2P Framework Mark Stamp Dept. of Computer Science San Jose State University
Rheeve: A Plug-n-Play Peer- to-Peer Computing Platform Wang-kee Poon and Jiannong Cao Department of Computing, The Hong Kong Polytechnic University ICDCSW.
Milos Kobliha Alejandro Cimadevilla Luis de Alba Parallel Computing Seminar GROUP 12.
Hands-On Microsoft Windows Server 2003 Networking Chapter 7 Windows Internet Naming Service.
The Open Grid Service Architecture (OGSA) Standard for Grid Computing Prepared by: Haoliang Robin Yu.
Biology.sdsc.edu CIPRes in Kepler: An integrative workflow package for streamlining phylogenetic data analyses Zhijie Guan 1, Alex Borchers 1, Timothy.
CONDOR DAGMan and Pegasus Selim Kalayci Florida International University 07/28/2009 Note: Slides are compiled from various TeraGrid Documentations.
January, 23, 2006 Ilkay Altintas
Apache Airavata GSOC Knowledge and Expertise Computational Resources Scientific Instruments Algorithms and Models Archived Data and Metadata Advanced.
RUNNING PARALLEL APPLICATIONS BEYOND EP WORKLOADS IN DISTRIBUTED COMPUTING ENVIRONMENTS Zholudev Yury.
Composing Models of Computation in Kepler/Ptolemy II
OSG Public Storage and iRODS
Scalable Systems Software Center Resource Management and Accounting Working Group Face-to-Face Meeting June 13-14, 2002.
Jan Storage Resource Broker Managing Distributed Data in a Grid A discussion of a paper published by a group of researchers at the San Diego Supercomputer.
Colin J. MacDougall.  Class of Systems and Applications  “Employ distributed resources to perform a critical function in a decentralized manner”  Distributed.
Grid Appliance – On the Design of Self-Organizing, Decentralized Grids David Wolinsky, Arjun Prakash, and Renato Figueiredo ACIS Lab at the University.
GT Components. Globus Toolkit A “toolkit” of services and packages for creating the basic grid computing infrastructure Higher level tools added to this.
1 School of Computer, National University of Defense Technology A Profile on the Grid Data Engine (GridDaEn) Xiao Nong
Software Design The Dynamic Model Design Sequence Diagrams and Communication Diagrams Instructor: Dr. Hany H. Ammar Dept. of Computer Science and Electrical.
Scalable Systems Software Center Resource Management and Accounting Working Group Face-to-Face Meeting October 10-11, 2002.
1 st December 2003 JIM for CDF 1 JIM and SAMGrid for CDF Mòrag Burgon-Lyon University of Glasgow.
SAM and D0 Grid Computing Igor Terekhov, FNAL/CD.
Accelerating Scientific Exploration Using Workflow Automation Systems Terence Critchlow (LLNL) Ilkay Altintas (SDSC) Scott Klasky(ORNL) Mladen Vouk (NCSU)
Interoperability between Scientific Workflows Ahmed Alqaoud, Ian Taylor, and Andrew Jones Cardiff University 10/09/2008.
CYBERINFRASTRUCTURE FOR THE GEOSCIENCES Data Replication Service Sandeep Chandra GEON Systems Group San Diego Supercomputer Center.
1 Ilkay ALTINTAS - July 24th, 2007 Ilkay ALTINTAS Director, Scientific Workflow Automation Technologies Laboratory San Diego Supercomputer Center, UCSD.
1 MSc Project Yin Chen Supervised by Dr Stuart Anderson 2003 Grid Services Monitor Long Term Monitoring of Grid Services Using Peer-to-Peer Techniques.
Kelly Davis and Tom Goodale Architecture of GAT Kelly Davis and Tom Goodale and
 Apache Airavata Architecture Overview Shameera Rathnayaka Graduate Assistant Science Gateways Group Indiana University 07/27/2015.
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
A Collaborative Framework for Scientific Data Analysis and Visualization Jaliya Ekanayake, Shrideep Pallickara, and Geoffrey Fox Department of Computer.
Architecture Models. Readings r Coulouris, Dollimore and Kindberg Distributed Systems: Concepts and Design Edn. 3 m Note: All figures from this book.
ICCS WSES BOF Discussion. Possible Topics Scientific workflows and Grid infrastructure Utilization of computing resources in scientific workflows; Virtual.
What is SAM-Grid? Job Handling Data Handling Monitoring and Information.
SAN DIEGO SUPERCOMPUTER CENTER Inca TeraGrid Status Kate Ericson November 2, 2006.
Kepler includes contributors from GEON, SEEK, SDM Center and Ptolemy II, supported by NSF ITRs (SEEK), EAR (GEON), DOE DE-FC02-01ER25486.
GRIDS Center Middleware Overview Sandra Redman Information Technology and Systems Center and Information Technology Research Center National Space Science.
Enabling e-Research in Combustion Research Community T.V Pham 1, P.M. Dew 1, L.M.S. Lau 1 and M.J. Pilling 2 1 School of Computing 2 School of Chemistry.
Toward interactive visualization in a distributed workflow Steven G. Parker Oscar Barney Ayla Khan Thiago Ize Steven G. Parker Oscar Barney Ayla Khan Thiago.
GCE Shell? GGF6 Chicago October Geoffrey Fox Marlon Pierce Indiana University
Recording Actor Provenance in Scientific Workflows Ian Wootten, Shrija Rajbhandari, Omer Rana Cardiff University, UK.
Super Computing 2000 DOE SCIENCE ON THE GRID Storage Resource Management For the Earth Science Grid Scientific Data Management Research Group NERSC, LBNL.
Satisfying Requirements BPF for DRA shall address: –DAQ Environment (Eclipse RCP): Gumtree ISEE workbench integration; –Design Composing and Configurability,
Ocean Observatories Initiative OOI Cyberinfrastructure Life Cycle Objectives Review January 8-9, 2013 Scientific Workflows for OOI Ilkay Altintas Charles.
Holding slide prior to starting show. Lessons Learned from the GECEM Portal David Walker Cardiff University
Grid Activities in CMS Asad Samar (Caltech) PPDG meeting, Argonne July 13-14, 2000.
Workflow-Driven Science using Kepler Ilkay Altintas, PhD San Diego Supercomputer Center, UCSD words.sdsc.edu.
Physical Oceanography Distributed Active Archive Center THUANG June 9-13, 20089th GHRSST-PP Science Team Meeting GHRSST GDAC and EOSDIS PO.DAAC.
VIEWS b.ppt-1 Managing Intelligent Decision Support Networks in Biosurveillance PHIN 2008, Session G1, August 27, 2008 Mohammad Hashemian, MS, Zaruhi.
Composing Web Services and P2P Infrastructure. PRESENTATION FLOW Related Works Paper Idea Our Project Infrastructure.
Building Distributed Educational Applications using P2P
Duncan MacMichael & Galen Deal CSS 534 – Autumn 2016
Self Healing and Dynamic Construction Framework:
Comparison of LAN, MAN, WAN
GGF10 Workflow Workshop Summary
Presentation transcript:

6th Biennial Ptolemy Miniconference Berkeley, CA May 12, 2005 Distributed Computing in Kepler Ilkay Altintas Lead, Scientific Workflow Automation Technologies Laboratory San Diego Supercomputer Center, UCSD (Joint work with Matthew Jones)

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Distributed Computation is a Requirement in Scientific Computing Increasing need for data and compute capabilities Data and computation should be combined for success! HEC + Data management/integration Picture from: Fran BERMAN Scientific workflows do scientific computing!

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Kepler and Grid Systems -- Early Efforts -- Some Grid actors in place Globus Job Runner, GridFTP-based file access, Proxy Certificate Generator For one job execution! Can be iterated… SRB support Interaction with Nimrod and APST Grid workflow pattern: STAGE FILES -> EXECUTE -> FETCH FILES Execute==Schedule -> Monitor & Recover Issues: Data and process provenance, user interaction, reporting and logging

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas NIMROD and APST GOAL: To use the expertise in scheduling and job maintenance

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Distributed Computing is Team Work Login to, create, join Grids & role-based access Access data Execute services Discover & use existing workflows Design, share, annotate, run and register workflows So our distributed computing framework should support collaborations! …as well as it should keep control of scheduling and provenance information…

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Goals and Requirements Two targets: Distributing execution Users can configure Kepler Grid access and execution parameters Kepler should manage the orchestration of distributed nodes. Kepler will have the ability to do failure recovery Users can be able to detach from the workflow instance after they and then connect again Supporting on the fly online collaborations Users can log into Kepler Grid and form groups Users can specify who can share the execution

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Peer-to-Peer System Satisfies These Goals A peer-to-peer network: Many or all of the participating hosts act both as client and server in the communication The JXTA framework provides: Peers Peer Groups Pipes Messages Queries and responses for metadata Requests and responses to move workflows and workflow components as.ksw files Data flow messages in executing workflows

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Creating KeplerGrid using P2P Technology Setting up Grid parameters Register as a peer Configure

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Creating KeplerGrid using P2P Technology Creating, Joining & Leaving Grids

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas P2P/JXTA Director Decides on the overall execution schedule Communicates with different nodes (peers) in the Grid Submits distributable jobs to remote nodes Can deduce if an actor can run remotely from its metadata Configuration parameters: Group to join Can have multiple models: Using a “master peer” and static scheduling is the current focus Work in progress… Creating KeplerGrid using P2P Technology Distributing Computation on a Specific Grid

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Built in services for handling failures and resubmission Checkpointing Store data where you execute it & send back metadata The “master peer” collects the provenance information How can we do it without having a global job database? Work in progress… Creating KeplerGrid using P2P Technology Provenance, Execution Logs and Failure Recovery

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas Status of Design and Implementation Initial tests with Grid creation, peer registration and discovery Start with a basic execution model extending SDF Need to explore different execution models More dynamic models seem more suitable Big design decisions to think on: What to stage to remote nodes Scalability Detachability Certification and security

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas To sum up… Just distributing the execution is not enough Need to think about the usability of it! Need to have sub-services using the JXTA model for peer discovery, data communication, logging, failure recovery. Might need more than one domain for different types of distributed workflows

UCSD SAN DIEGO SUPERCOMPUTER CENTER Ilkay Altintas +1 (858) Questions?.. Thanks!