Tuning the Performance of I/O-Intensive Parallel Applications
Anurag Acharya,
Mustafa Uysal,
Robert Bennett,
Assaf Mendelson,
Michael Beynon,
Jeff Hollingsworth,
Joel Saltz,
Alan Sussman.
To appear in IOPADS'96
Abstract:
Getting good I/O performance from parallel programs is a critical
problem for many application domains. In this paper, we report our
experience tuning the I/O performance of four application programs
from the areas of sensor data processing and linear algebra. After
tuning, three of the four applications achieve effective I/O rates of
over 100MB/s, on 16 processors. The total volume of I/O required by
the programs ranged from about 75MB to over 200GB. We report the
lessons learned in achieving high I/O performance from these
applications, including the need for code restructuring, local disks
on every node and overlapping I/O with computation. We also report our
experience on achieving high performance on peer-to-peer
configurations. Finally, we comment on the necessity of complex I/O
interfaces like collective I/O and strided requests to achieve high
performance.
Postscript
(compressed 137K)
A previous version appeared as
CRPC TR95632-S
(compressed 153 K)