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SCALA: A framework for performance evaluation of scalable computing

  • Xian-He Sun
  • Mario Pantano
  • Thomas Fahringer
  • Zhaohua Zhan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1586)

Abstract

Conventional performance environments are based on profiling and event instrumentation. It becomes problematic as parallel systems scale to hundreds of nodes and beyond. A framework of developing an integrated performance modeling and prediction system, SCALability Analyzer (SCALA), is presented in this study. In contrast to existing performance tools, the program performance model generated by SCALA is based on scalability analysis. SCALA assumes the availability of modern compiler technology, adopts statistical methodologies, and has the support of browser interface. These technologies, together with a new approach of scalability analysis, enable SCALA to provide the user with a higher and more intuitive level of performance analysis. A prototype SCALA system has been implemented. Initial experimental results show that SCALA is unique in its ability of revealing the scaling properties of a computing system.

Keywords

Execution Time Problem Size Scalability Analysis Graphical Object Range Comparison 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Xian-He Sun
    • 1
  • Mario Pantano
    • 2
  • Thomas Fahringer
    • 3
  • Zhaohua Zhan
    • 1
  1. 1.Department of Computer ScienceLouisiana State University
  2. 2.Department of Computer ScienceUniversity of IllinoisUrbana
  3. 3.Institute for Software Technology and Parallel SystemsUniversity of ViennaViennaAustria

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