Efficient Discovery of Loop Nests in Execution Traces

Execution and communication traces are central to performance modeling and analysis. Since the traces can be very long, meaningful compression and extraction of representative behavior is important. Commonly used compression procedures identify repeating patterns in sections of the input string and replace each instance with a representative symbol. This can prevent the identification of long repeating sequences corresponding to outer loops in a trace. This paper introduces and analyzes a framework for identifying the maximal loop nest from a trace. The discovery of loop nests makes construction of compressed representative traces straightforward. The paper also introduces a greedy algorithm for fast ``near optimal´´ loop nest discovery with well defined bounds. Results of compressing MPI communication traces of NAS parallel benchmarks show that both algorithms identified the basic loop structures correctly. The greedy algorithm was also very efficient with an average processing time of 16.5 seconds for an average trace length of 71695 MPI events.