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Title: Scalability of parallel algorithm-machine combinations

Journal Article · · IEEE Transactions on Parallel and Distributed Systems
DOI: https://doi.org/10.1109/71.285606 · OSTI ID:6036379
 [1];  [2]
  1. NASA Langley Research Center, Hampton, VA (United States); Louisiana State Univ., Baton Rouge, LA (United States)
  2. Michigan State Univ., East Lansing, MI (United States)
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Scalability has become an important consideration in parallel algorithm and machine designs. The word scalable, or scalability, has been widely and often used in the parallel processing community. However, there is no adequate, commonly accepted definition of scalability available. Scalabilities of computer systems and programs are difficult to quantify, evaluate, and compare. In this paper, scalability is formally defined for algorithm-machine combinations. A practical method is proposed to provide a quantitative measurement of the scalability. The relation between the newly proposed scalability and other existing parallel performance metrics is studied. A harmony between speedup and scalability has been observed. Theoretical results show that a large class of algorithm-machine combinations is scalable and the scalability can be predicted through premeasured machine parameters. Two algorithms have been studied on an nCUBE 2 multicomputer and on a MasPar MP-1 computer. These case studies have shown how scalabilities can be measured, computed, and predicted. In addition, performance instrumentation and visualization tools also have been used and developed to understand the scalability related behavior.

Research Organization:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
W-7405-ENG-82
OSTI ID:
6036379
Report Number(s):
IS-M--666; ON: DE91011902
Journal Information:
IEEE Transactions on Parallel and Distributed Systems, Journal Name: IEEE Transactions on Parallel and Distributed Systems Journal Issue: 6 Vol. 5; ISSN 1045-9219
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

References (13)

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Visualizing the performance of parallel programs journal September 1991
Another view on parallel speedup conference November 1990
Development of Parallel Methods for a $1024$-Processor Hypercube
  • Gustafson, John L.; Montry, Gary R.; Benner, Robert E.
  • SIAM Journal on Scientific and Statistical Computing, Vol. 9, Issue 4 https://doi.org/10.1137/0909041
journal July 1988
Scalability of parallel machines journal March 1991
Analysis of scalability of parallel algorithms and architectures conference January 1991
Validity of the single processor approach to achieving large scale computing capabilities conference January 1967
Reevaluating Amdahl's law journal May 1988
Modeling the interaction of light between diffuse surfaces journal July 1984

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