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article · CLEI electronic journal · 1998

User-Level Parallel File I/O

Ernst L. Leiss, Yili Wang

Cited by 1Open access

Abstract


 
 
 
 Parallel disk I/O subsystems are becoming more important in today’s large-scale parallel machines. Parallel disk systems provide a significant boost in I/O performance reducing the gap between processor and disk speeds. We describe a Unix-like file I/O user interface, implemented in a parallel file I/O subsystem on an MIMD machine, the nCUBE 2. Based on message passing, we develop parallel disk read/write algorithms to achieve higher parallelism when more disk drives are used. We use the closed queuing network model to analyze the effect of some tunable system parameters for our parallel file system. We then performed simulation experiments in order to obtain more realistic performance data, by comparing the original vendor-supplied file system with ours. The results indicate that the speedup in I/O performance is almost equal to the number of disk drives we use. Thus, our user-level parallel file I/O approach will provide scalable I/O performance.
 
 
 

Cite this paper

APA 7

Leiss, E. L., & Wang, Y. (1998). User-Level Parallel File I/O. CLEI electronic journal, 1(1). https://doi.org/10.19153/cleiej.1.1.5

MLA 9

Leiss, Ernst L., and Yili Wang. “User-Level Parallel File I/O.” CLEI electronic journal, vol. 1, no. 1, 1998, https://doi.org/10.19153/cleiej.1.1.5.

Chicago

Leiss, Ernst L., and Yili Wang. 1998. “User-Level Parallel File I/O.” CLEI electronic journal 1 (1). https://doi.org/10.19153/cleiej.1.1.5.

Harvard

Leiss, E.L. and Wang, Y. (1998) ‘User-Level Parallel File I/O’, CLEI electronic journal, 1(1). Available at: https://doi.org/10.19153/cleiej.1.1.5.

BibTeX
@article{leiss1998user,
  title = {{User-Level Parallel File I/O}},
  author = {Leiss, Ernst L. and Wang, Yili},
  journal = {CLEI electronic journal},
  volume = {1},
  number = {1},
  year = {1998},
  doi = {10.19153/cleiej.1.1.5}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

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