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https://hdl.handle.net/2142/72078
Description
Title
Disk I/O in High-Performance Computing Systems
Author(s)
Jensen, David Wayne
Issue Date
1993
Doctoral Committee Chair(s)
Reed, Daniel
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Computer Science
Abstract
There exists an increasing disparity between the performance of high-performance computers and disk I/O systems. This divergence in performance signifies that the I/O system will become an increasing bottleneck in future computer systems. With such a bottleneck, a program's execution time on these systems could approach the associated file access time in the limiting case. We review the evolution of I/O architectures and characterize the access patterns of requests to those I/O systems. We apply this information to investigate the I/O performance of a multiple disk system in a multiprocessor system.
Today's disk subsystems typically provide good I/O performance for only sequential access. Our study uses a simulated multiprocessor and multiple disk system architecture. I/O and memory traffic is combined in the system's packet-switched, multistage interconnection network. Our investigation first considers the effects of the I/O traffic on memory access in the multistage network. We then use a set of synthetic access patterns to evaluate the potential I/O performance. We consider the effectiveness of using custom mappings of file data to disks to support non-sequential I/O in this multiprocessor system. Not only do we investigate the more traditional workload of multiple processors accessing separate files, we also study the I/O characteristics of multiple processors accessing a single file.
Our experiments show the I/O access pattern, the data placement on disks, the number of disks, and the I/O request rate, all interact to determine the performance of such a multiple disk I/O system. We found no single data placement on the multiple disks can provide good I/O performance for all workload cases. Similarly, a different set of data placement guidelines were identified for multiple processors accessing a single file than those identified for the more conventional access of multiple files.
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