CT PROJECT

1. CT PROJECT ESTO An Astronomical Image Mosaic Service for theNational Virtual Observatoryhttp://montage.ipac.caltech.edu/

2. Attila Bergou - JPL Bruce Berriman - IPAC Ewa Deelman - ISI John Good - IPAC Joseph C. Jacob - JPL Daniel S. Katz - JPL Carl Kesselman - ISI Anastasia Laity - IPAC Thomas Prince - Caltech Gurmeet Singh - ISI Mei-Hui Su - ISI Roy Williams - CACR Contributors

3. What is Montage? • Delivers custom, science grade image mosaics • User specifies projection, coordinates, spatial sampling, mosaic size, image rotation • Preserve astrometry & flux • Modular “toolbox” design • Loosely-coupled Engines for Image Reprojection, Background Removal, Co-addition • Control testing and maintenance costs • Flexibility; e.g., custom background algorithm; use as a reprojection and co-registration engine • Implemented in ANSI C for portability • Public service will be deployed on the Teragrid • Order mosaics through web portal

4. Public Release of Montage • Version 1.7.1 and User’s Guide available for download at http://montage.ipac.caltech.edu/ • Emphasizes accuracy in photometry and astrometry • Images processed serially • Tested and validated on 2MASS 2IDR images on Linux Red Hat 8.0 (Kernel release 2.4.18-14) on a 32-bit processor • Tested on 10 WCS projections with mosaics smaller than 2 x 2 degrees and coordinate transformations Equ J2000 to Galactic and Ecliptic • Extensively tested • 2,595 test cases executed • 119 defects reported and 116 corrected • 3 remaining defects to be corrected in future Montage release

5. Applications of Montage • Large scale processing of the sky; e.g., Atlasmaker • Mosaics of the Infrared Sky • This is the age of Infrared Astronomy! • Infrared astronomers study regions much larger than covered by individual cameras ==> need to make mosaics to investigate star formation, redshift distribution of galaxies • Mosaics of the far infrared sky a primary data product of the SIRTF mission • Two SIRTF Legacy teams using Montage as a co-registration and mosaic engine to generate science mosaics, perform image simulations, mission planning & pipeline testing • Public Outreach - the wow factor! • Combine single color images in Photoshop • Example: back-lit display in NASA booth • See next image - Rho Ophiuchi

6. Rho Ophiuchi 324 2MASS images in each band => 972 imagesOn a 1 GHz Sun, mosaicking takes about 15 hours

7. Montage: The Grid Years • Re-projection is slow (100 seconds for one 1024 x 512 pixel 2MASS image on a single processor 1.4 GHz Linux box), so use parallelization inherent in design • Grid is an abstraction - array of processors, grid of clusters, … • Montage has modular design - run on any environment • Prototype architecture for ordering a mosaic through a web portal • Request processed on a computing grid • Prototype uses the Distributed Terascale Facility (Teragrid) • This is one instance of how Montage could run on a grid • Atlasmaker is another example of Montage parallelization

8. Montage: The Grid Years (cont.) • Prototype version of a methodology for running on any “grid environment” • Many parts of the process can be parallelized • Build a script to enable parallelization • Called a Directed Acyclical Graph (DAG) • Describes flow of data and processing • Describes which data are needed by which part of the job • Describes what is to be run and when • Standard tools can execute a DAG

9. Teragrid Cluster SDSC NCSA Using Montage Grid Prototype • Web service at JPL creates an abstract workflow description of Montage run (in XML) • Workflow description run through Pegasus to create concrete DAG • Pegasus includes transfer nodes in the concrete DAG for staging in the input image files and transferring out the generated mosaic • Concrete DAG submitted to Condor Region Name, Degrees JPL Abstract DAG Pegasus Concrete DAG Condor DAGMAN ISI Condor Pool

10. 3 3 2 2 3 1 2 1 1 Final Mosaic mConcatFit mProject 1 mProject 2 mProject 3 mAdd mBackground 1 mBackground 2 mBackground 3 mDiff 1 2 mDiff 2 3 D23 D12 a1x + b1y + c1 = 0 a2x + b2y + c2 = 0 a3x + b3y + c3 = 0 mFitplane D12 mFitplane D23 mBgModel ax + by + c = 0 dx + ey + f = 0 ax + by + c = 0 dx + ey + f = 0 Montage Workflow • Described as abstract DAG - specifies: • Input, output, and intermediate files • Processing jobs • Dependencies between them

11. Data Stage in nodes Montage compute nodes Data stage out nodes Registration nodes Montage – Concrete DAG (single pool) Example DAG for 10 input files mProject mDiff mFitPlane mConcatFit mBgModel mBackground mAdd

12. Montage Runs on the Teragrid • Test runs were done on the 1.5 degree x 1.5 degree area including M42 (Orion Nebula) • Required 113 input image files • Single pool DAG for SDSC consisted of 951 jobs • 117 were data transfer jobs • 113 for transferring the input image files • 3 for transferring other header files • 1 for transferring the final output mosaic • Run took 94 minutes

13. Montage Runs on the Teragrid (2) • Using same abstract DAG for multi pool DAG at SDSC and NCSA created 1202 jobs • 367 were data transfer jobs • Some of these jobs transferred multiple files • 249 of these 367 were inter pool data transfer jobs

14. Montage Computations • Building a mosaic from N 1024 x 512 pixel 2MASS images on a single processor 1.4 GHz Linux box takes roughly (N x 100) seconds • 98-99% of this time is in the reprojection, which can be perfectly parallelized (this doesn’t embarrass us)

15. Summary • Montage is a custom astronomical image mosaicking service that emphasizes astrometric and photometric accuracy • First public release, Montage_v1.7.1, available for download at the Montage website • A prototype Montage service has been deployed on the Teragrid; ties together distributed services at JPL, Caltech IPAC, and ISI • More on Montage at SC2003: • See ISI at ANL booth for demo of Pegasus portal running Montage on the Teragrid • See back-lit display of Montage images at NASA booth • Montage website: http://montage.ipac.caltech.edu/