Yogesh Simmhan, Maria Nieto-Santisteban, Roger Barga, Tamas Budavari, Laszlo Dobos, Nolan Li, Michael Shipway, Alexander S. Szalay, Ani Thakar, Jan Vandenberg, Alainna Wonders, Sue Werner, Richard Wilton, Dan Fay, Michael Thomassy, Catharine van Ingen, Jim Heasley, and Conrad Holmberg
Big data presents new challenges to both cluster infrastructure software and parallel application design. We present a set of software services and design principles for data intensive computing with petabyte data sets, named GrayWulf†. These services are intended for deployment on a cluster of commodity servers similar to the well-known Beowulf clusters. We use the Pan-STARRS system currently under development as an example of the architecture and principles in action.
In Hawaii International Conference on System Sciences (HICSS)
Publisher IEEE Computer Society
Copyright © 2007 IEEE. Reprinted from IEEE Computer Society. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Yogesh Simmhan, Roger Barga, Catharine van Ingen, Maria Nieto-Santisteban, Laszlo Dobos, Nolan Li, Michael Shipway, Alexander S. Szalay, Sue Werner, and Jim Heasley. GrayWulf: Scalable Software Architecture for Data Intensive Computing, Microsoft Research, 15 September 2008.