Distributed simulation performance data mining

The performance of logical process based distributed simulation (DS) protoc ols like Time Warp and Chandy/Misra/Bryant is influenced by a variety of fa ctors such as the event structure underlying the simulation model, the part itioning into submodels, the performance characteristics of the execution p latform, the implementation of the simulation engine and optimizations rela ted to the protocols. The mutual performance effects of parameters exhibit a prohibitively complex degree of interweaving, giving analytical performan ce investigations only relative relevance. Nevertheless: performance analys is is of utmost practical interest for the simulationist who wants to decid e on the suitability of a certain DS protocol for a specific simulation mod el before substantial efforts are invested in developing sophisticated DS c odes. Since DS performance prediction based on analytical models appears doubtful with respect to adequacy and accuracy, this work presents a prediction met hod based on the simulated execution of skeletal implementations of DS prot ocols. Performance data mining methods based on statistical analysis and a simulation tool for DS protocols have been developed for DS performance pre diction, supporting the simulationist in three types of decision problems: (i) given a simulation problem and parallel execution platform, which DS pr otocol promises best performance, (ii) given a simulation model and a DS st rategy, which execution platform is appropriate from the performance viewpo int, and (iii) what class of simulation models is best executed on a given multiprocessor using a certain DS protocol. Methodologically, skeletons of the most important variations of DS protocols are developed and executed in the N-MAP performance prediction environment. As a mining technique, perfo rmance data is collected and analyzed based on a full factorial design. The design predictor variables are used to explain DS performance. (C) 2001 El sevier Science B.V. All rights reserved.