Title :
Scalable performance visualization for data-parallel programs
Author :
Hackstadt, Steven T. ; Malony, Allen D. ; Mohr, Bernd
Author_Institution :
Dept. of Comput. & Inf. Sci., Oregon Univ., Eugene, OR, USA
Abstract :
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++
Keywords :
computer graphics; parallel languages; parallel programming; program diagnostics; visual programming; Dataparallel C; data-parallel programming; data-parallel programs; distribution semantics; pC++; performance behavior; problem size; scalable performance visualization; scalable performance visualizations; three-dimensional graphics; visual scalability properties; Computer hacking; Concurrent computing; Contracts; Data analysis; Data visualization; Displays; Graphics; Information science; Robustness; Scalability;
Conference_Titel :
Scalable High-Performance Computing Conference, 1994., Proceedings of the
Conference_Location :
Knoxville, TN
Print_ISBN :
0-8186-5680-8
DOI :
10.1109/SHPCC.1994.296663
