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

COMPUTER programming; ELECTRONIC data processing; COMPUTER algorithms; MATHEMATICAL models

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. [Copyright &y& Elsevier]

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