Scalable Message Passing in Panda
Y. Chen,
M. Winslett,
K. E. Seamons,
S. Kuo, Y. Cho, and M. Subramaniam, University of Illinois
Abstract:
To provide high performance for applications with a wide variety of
i/o requirements and to support many different parallel platforms, the
design of a parallel i/o system must provide for efficient utilization
of available bandwidth both for disk traffic and for message passing.
In this paper we discuss the message-passing scalability of the
server-directed i/o architecture of Panda, a library for synchronized
i/o of multidimensional arrays on parallel platforms. We show how to
improve i/o performance in situations where message-passing is a
bottleneck, by combining the server-directed i/o strategy for highly
efficient use of available disk bandwidth with new mechanisms to
minimize internal communication and computation overhead in Panda. We
present experimental results that show that with these improvements,
Panda will provide high i/o performance for a wider range of
applications, such as applications running with slow interconnects,
applications performing i/o operations on large numbers of arrays, or
applications that require drastic data rearrangements as data are
moved between memory and disk (e.g., array transposition). We also
argue that in the future, the improved approach to message-passing
will allow Panda to support applications that are not closely
synchronized or that run in heterogeneous environments.
David Kotz --
Last modified: Wed Jan 31 16:04:25 1996