David Kotz papers for project 'armada'

Improving data access for computational grid applications

Sun, 01 Jan 2006 00:00:00

Ron Oldfield and David Kotz. Improving data access for computational grid applications. Cluster Computing, volume 9, number 1, pages 79–99. Springer, January 2006. doi:10.1007/s10586-006-4899-7.

Abstract:

High-performance computing increasingly occurs on “computational grids” composed of heterogeneous and geographically distributed systems of computers, networks, and storage devices that collectively act as a single “virtual” computer. A key challenge in this environment is to provide efficient access to data distributed across remote data servers. Our parallel I/O framework, called Armada, allows application and data-set providers to flexibly compose graphs of processing modules that describe the distribution, application interfaces, and processing required of the dataset before computation. Although the framework provides a simple programming model for the application programmer and the data-set provider, the resulting graph may contain bottlenecks that prevent efficient data access. In this paper, we present an algorithm used to restructure Armada graphs that distributes computation and data flow to improve performance in the context of a wide-area computational grid.

Efficient I/O for Computational Grid Applications

Thu, 01 May 2003 00:00:00

Ron Oldfield. Efficient I/O for Computational Grid Applications. PhD thesis, Dartmouth Computer Science, Hanover, NH, May 2003. Available as Dartmouth Computer Science Technical Report TR2003-459.

Abstract:

High-performance computing increasingly occurs on “computational grids” composed of heterogeneous and geographically distributed systems of computers, networks, and storage devices that collectively act as a single “virtual” computer. A key challenge in this environment is to provide efficient access to data distributed across remote data servers. This dissertation explores some of the issues associated with I/O for wide-area distributed computing and describes an I/O system, called Armada, with the following features: a framework to allow application and dataset providers to flexibly compose graphs of processing modules that describe the distribution, application interfaces, and processing required of the dataset before or after computation; an algorithm to restructure application graphs to increase parallelism and to improve network performance in a wide-area network; and a hierarchical graph-partitioning scheme that deploys components of the application graph in a way that is both beneficial to the application and sensitive to the administrative policies of the different administrative domains. Experiments show that applications using Armada perform well in both low- and high-bandwidth environments, and that our approach does an exceptional job of hiding the network latency inherent in grid computing.

Using the Emulab network testbed to evaluate the Armada I/O framework for computational grids

Sun, 01 Sep 2002 00:00:00

Ron Oldfield and David Kotz. Using the Emulab network testbed to evaluate the Armada I/O framework for computational grids. Technical Report number TR2002-433, Dartmouth Computer Science, Hanover, NH, September 2002.

Abstract:

This short report describes our experiences using the Emulab network testbed at the University of Utah to test performance of the Armada framework for parallel I/O on computational grids.

Armada: a parallel I/O framework for computational grids

Fri, 01 Mar 2002 00:00:00

Ron Oldfield and David Kotz. Armada: a parallel I/O framework for computational grids. Future Generation Computing Systems (FGCS), volume 18, number 4, pages 501–523. Elsevier Science Press, March 2002. doi:10.1016/S0167-739X(01)00076-0.

Abstract:

The Armada framework for parallel I/O on computational grids

Tue, 01 Jan 2002 00:00:00

Ron Oldfield and David Kotz. The Armada framework for parallel I/O on computational grids. Proceedings of the USENIX Conference on File and Storage Technologies (FAST). USENIX Association, January 2002. Work-in-progress report.

Scientific Applications using Parallel I/O

Sat, 01 Sep 2001 00:00:00

Ron Oldfield and David Kotz. Scientific Applications using Parallel I/O. High Performance Mass Storage and Parallel I/O: Technologies and Applications, chapter 45, pages 655–666. Edited by Hai Jin, Toni Cortes, and Rajkumar Buyya. Wiley-IEEE Press, September 2001. ISBN13: 978-0-471-20809-9.

Abstract:

Scientific applications are increasingly being implemented on massively parallel supercomputers. Many of these applications have intense I/O demands, as well as massive computational requirements. This paper is essentially an annotated bibliography of papers and other sources of information about scientific applications using parallel I/O.

Armada: A parallel file system for computational grids

Tue, 01 May 2001 00:00:00

Ron Oldfield and David Kotz. Armada: A parallel file system for computational grids. Proceedings of the IEEE/ACM International Symposium on Cluster Computing and the Grid (ccGrid), pages 194–201. IEEE, Brisbane, Australia, May 2001. doi:10.1109/CCGRID.2001.923193.

Abstract:

High-performance distributed computing appears to be shifting away from tightly-connected supercomputers to computational grids composed of heterogeneous systems of networks, computers, storage devices, and various other devices that collectively act as a single geographically distributed virtual computer. One of the great challenges for this environment is providing efficient parallel data access to remote distributed datasets. In this paper, we discuss some of the issues associated with parallel I/O and computatational grids and describe the design of a flexible parallel file system that allows the application to control the behavior and functionality of virtually all aspects of the file system.

Applications of Parallel I/O

Sat, 01 Aug 1998 00:00:00

Ron Oldfield and David Kotz. Applications of Parallel I/O. Technical Report number PCS-TR98-337, Dartmouth Computer Science, August 1998. Supplement to PCS-TR96-297.

Abstract:

Applications of Parallel I/O

Tue, 01 Oct 1996 00:00:00

David Kotz. Applications of Parallel I/O. Technical Report number PCS-TR96-297, Dartmouth Computer Science, October 1996. Release 1.

Abstract: