Milkyway@Home for GPUs

About Milkyway@Home for GPUs

The goal of Milkyway@Home for GPUs is to use the BOINC platform to harness volunteered computing resources in creating a highly accurate three dimensional model of the Milky Way galaxy using data gathered by the Sloan Digital Sky Survey. This project enables research in both astroinformatics and computer science.

In computer science, the project is investigating different optimization methods which are resilient to the fault-prone, heterogeneous and asynchronous nature of Internet computing; such as evolutionary and genetic algorithms, as well as asynchronous newton methods. While in astroinformatics, Milkyway@Home is generating highly accurate three dimensional models of the Sagittarius stream, which provides knowledge about how the Milky Way galaxy was formed and how tidal tails are created when galaxies merge.

MilkyWay@Home is a joint effort between Rensselaer Polytechnic Institute's departments of Computer Science and Physics, Applied Physics and Astronomy. Feel free to contact us via our forums, or email astro [at] cs [dot] rpi [dot] edu.

Join Milkyway@Home for GPUs

This project uses BOINC. If you're already running BOINC, select Attach to Project. If not, download BOINC.
When prompted, enter http://milkyway.cs.rpi.edu/milkyway_gpu/
If you're running a command-line or pre-5.0 version of BOINC, create an account first.
If you have any problems, get help here.

Returning participants

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Community and Information

Publications

Thanks to the support of our users, this work has facilitated the following publications:

Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Kristopher Dawsey, Warren Hayashi, Jonathan Purnell, Boleslaw Szymanski, Carlos A. Varela, Benjamin Willett, and James Wisniewski. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. Astrophysical Journal, 683:750-766, 2008.
Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy using Volunteer Computing. In Genetic and Evolutionary Computation Conference (GECCO 2008), Atlanta, Georgia, pages 921-928, July 2008.
Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. Asynchronous Genetic Search for Scientific Modeling on Large-Scale Heterogeneous Environments. In Proceedings of the 17th International Heterogeneity in Computing Workshop (HCW/IPDPS'08), Miami, FL, pages 12pp, April 2008. IEEE.
Boleslaw Szymanski, Travis Desell, and Carlos A. Varela. The Effect of Heterogeneity on Asynchronous Panmictic Genetic Search. In Proc. of the Seventh International Conference on Parallel Processing and Applied Mathematics (PPAM'2007), LNCS, Gdansk, Poland, September 2007.
Travis Desell, Nathan Cole, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski, and Carlos A. Varela. Distributed and Generic Maximum Likelihood Evaluation. In 3rd IEEE International Conference on e-Science and Grid Computing (eScience2007), Bangalore, India, pages 337-344, December 2007. Best paper finalist.

People

MilkyWay@Home is currently run by:

Travis Desell, Graduate Research Assistant in Computer Science
Dave Przybylo, Undergraduate Research Assistant in Computer Science
Nathan Cole, Graduate Research Assistant in Physics, Applied Physics and Astronomy
Malik Magdon-Ismail, Associate Professor of Computer Science
Heidi Newberg, Associate Professor of Physics, Applied Physics, and Astronomy
Boleslaw Szymanski, Claire and Roland Schmitt Distinguished Professor of Computer Science
Carlos Varela, Associate Professor of Computer Science

With previous support from:

Joe Doran, Undergraduate Research Assistant in Computer Science

Support

This material is based upon work supported by the National Science Foundation under Grant Nos. 0612213, 0607618 and 0448407.

Data-Driven Discovery of the Milky Way Origin and Evolution from the Sloan Digital Sky Survey, NSF IIS Grant #0612213, started 07/26/2006. Principal Investigators: Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos Varela.
Revealing the Structure of the Galactic Halo through Statistical Analysis - Middle School Teacher Training, NSF AST Grant #0607618, started 07/15/2006. Prinicpal Investigators: Heidi Newberg, Malik Magdon-Ismail.
Middleware and Programming Technology for Grid Computing, NSF CAREER Grant #0448407, started 01/21/2005. Principal Investigator: Carlos Varela.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.