Analyzing PICL trace data with MEDEA

Abstract

Executiontraces and performancestatistics can be collected forparallel applications on a variety of multiprocessor platforms by using the Portable Instrumented Communication Library (PICL). The static and dynamic performance characteristics of performance data can be analyzed easily and effectively with the facilities provided within the MEasurements Description Evaluation and Analysis tool (MEDEA). This report describes the integration of the PICL trace file format into MEDEA. A case study is then outlined that uses PICL and MEDEA to characterize the performance of a parallel benchmark code executed on different hardware platforms and using different parallel algorithms and communication protocols.