Scalable Performance Visualization for Data-Parallel Programs

Developing robust techniques for visualizing the performance behavior of parallel programs that can scale in problem size and/or number of processors remains a challenge. We present several performance visualization techniques based on the context of data-parallel programming and execution that demonstrate good visual scalability properties. These techniques are a result of utilizing the structural and distribution semantics of data-parallel programs as well as sophisticated three-dimensional graphics. A categorization and examples of scalable performance visualizations are given for programs, written in Dataparallel C and pC++