A pilot study to compare programming effort for two parallel programming models

  • Authors:

  • Lorin Hochstein;Victor R. Basili;Uzi Vishkin;John Gilbert

  • Affiliations:

  • University of Nebraska, Lincoln, Department of Computer Science and Engineering, United States;University of Maryland, Computer Science Department, United States;University of Maryland, Institute for Advanced Computer Studies, United States;University of California, Santa Barbara, Computer Science Department, United States

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2008

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Abstract

Context: Writing software for the current generation of parallel systems requires significant programmer effort, and the community is seeking alternatives that reduce effort while still achieving good performance. Objective: Measure the effect of parallel programming models (message-passing vs. PRAM-like) on programmer effort. Design, setting, and subjects: One group of subjects implemented sparse-matrix dense-vector multiplication using message-passing (MPI), and a second group solved the same problem using a PRAM-like model (XMTC). The subjects were students in two graduate-level classes: one class was taught MPI and the other was taught XMTC. Main outcome measures: Development time, program correctness. Results: Mean XMTC development time was 4.8h less than mean MPI development time (95% confidence interval, 2.0-7.7), a 46% reduction. XMTC programs were more likely to be correct, but the difference in correctness rates was not statistically significant (p=.16). Conclusions: XMTC solutions for this particular problem required less effort than MPI equivalents, but further studies are necessary which examine different types of problems and different levels of programmer experience.