Visualizing the memory performance of parallel programs with Chiron

Abstract

This thesis describes Chiron, visualization system which helps programmers detect memory system bottlenecks in their shared-memory parallel applications. Chiron is different from most other performance debugging tools in that it uses three-dimensional graphics techniques to display vast amounts of memory-performance data. Both code-and data-oriented information can be presented in several views. These views have been designed to help the user detect problems which cause coherence interference or replacement interference. Chiron’s interactive user-interface enables the user to manipulate the views and home in on features which indicate memory system bottlenecks. The visualized data can be augmented with more detailed numerical and correlations between the separate views can be displayed. The effectiveness of Chiron is illustrated in this thesis by means of three case studies.