darrell@sequoia.ucsc.edu (Darrell Long) (10/16/90)
Archive-name: swift/15-Oct-90
Original-posting-by: darrell@sequoia.ucsc.edu (Darrell Long)
Original-subject: TR available
Archive-site: midgard.ucsc.edu [128.114.134.15]
Archive-directory: /pub/tr
Reposted-by: emv@math.lsa.umich.edu (Edward Vielmetti)
% I keep a list of ftp'able reports on midgard.ucsc.edu. If you'd like me to
% add your reports to that list, send me a note. --DL
The following technical report is available by anonymous FTP from
midgard.ucsc.edu (128.114.134.15) as pub/tr/ucsc-crl-89-04.tar.Z
A printed copy of the report can be obtained by sending $4 to:
Jean McKnight
Technical Librarian
Baskin Center for Computer Engineering & Information Sciences
Applied Sciences Building
University of California
Santa Cruz, CA 95064
Swift: A Storage Architecture for Large Objects
Luis-Felipe Cabrera
IBM Almaden Research Center
Darrell D. E. Long
University of California, Santa Cruz
ABSTRACT
Managing large objects with high data rate requirements is
difficult for current computing systems. The increasing
disparity between the fastest network transfer rate and the
fastest disk transfer rate requires resolution. We present an
architecture, called Swift, that addresses the problem of storing
and retrieving, at high data rates, large data objects from
slower secondary storage. Applications range from visualization
of scientific computations to real-time storage and retrieval of
color video.
Swift addresses this issue by exploiting the available
interconnection capacity and by using several slower storage
devices concurrently. We study the performance characteristics
of a local-area instance of Swift using a parametric simulation
model. We consider a system of high-performance work stations
connected to multiple storage agents by a high-speed local area
network. Our simulation shows Swift compares favorably with
other concurrent I/O architectures, such as disk arrays, in terms
of maximum aggregate data rate and resource requirements.
Keywords: high-performance storage systems, high data rates, disk
striping, high-speed networks, distributed systems, data
redundancy, server resiliency.