The tuning problem on pipelines

Abstract

Performance analysis and prediction is an important factor determining the efficiency of parallel programs. Considerable efforts have been made both in pure theoretical analysis and in practical automatic profiling. Unfortunately, contributions in one area seem to ignore the results of the other. We introduce a general performance prediction methodology based on the integration of analytical models and profiling tools. According to this approach we have developed a tool that automatically solves the prediction of the parameters for optimal executions of parallel pipeline algorithms. The accuracy of the proposal has been tested on a CRAY T3E for pipeline algorithms solving combinatorial optimization problems. The results obtained suggest that the technique could be successfully ported to other paradigms.