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The Distributed-Parallel Storage System (DPSS) Home Page

Data Intensive Distributed Computing Group
Lawrence Berkeley National Laboratory


The Distributed-Parallel Storage System (DPSS) is a scalable, high-performance, distributed-parallel data storage system orginally developed as part of the DARPA -funded MAGIC Testbed, with additional support from the U.S. Dept. of Energy, Energy Research Division, Mathematical, Information, and Computational Sciences Office.

The DPSS is a data block server, which provides high-performance data handling and architecture for building high-performance storage systems from low-cost commodity hardware components. This technology has been quite successful in providing an economical, high-performance, widely distributed, and highly scalable architecture for caching large amounts of data that can potentially be used by many different users.

Current performance results are 980 Mbps across a LAN and 570 Mbps across a WAN.


About the DPSS


Using and Installing a DPSS


DPSS Integration:


DPSS Applications

  • A Medical Imaging application using the DPSS and ImgLib
  • Terravision: The terrain navigation program that was the initial target application for the DPSS.
  • DIV : A large image viewing application from the EROS Data Center.
  • A High Energy Physics data processing application.
  • Most of these applications are examples of the Wide Area Large Data Object architecture (WALDO) that we have been developing.



You may also perform a keyword search on this documentation.

(*) Some of these pages have restricted access. If you don't have access to these pages, contact Brian Tierney (BLTierney@lbl.gov), and tell me why you'd like access and what hosts you will be connecting from.

DPSS Private pages


COPYRIGHT NOTICE: Image Server System (ISS) and Distributed Parallel Storage System (DPSS) are Copyright © 1994 by Lawrence Berkeley Laboratory


This page is the responsiblity of Brian L. Tierney. (BLTierney@lbl.gov). Support Credits identify the funding sources and the organizational context of the work described in this document.
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Credits: The research and development of the Distributed Systems Department i s funded by the U.S. Dept. of Energy, Office of Science, Office of Advanced Scie ntific Computing Research, Mathematical, Information, and Computational Sciences Division

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This page last modified: Wednesday, 16-Jun-2004 16:54:35 PDT