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Data-centric Parallel Debugging Technique for Petascale Computers
SESSION: Doctoral Research Showcase (2 of 2)
EVENT TYPE: Doctoral Research Showcase
TIME: 4:00PM - 4:15PM
SESSION CHAIR: Volodymyr Kindratenko
ABSTRACT: This research addresses three main sources of challenge in debugging parallel applications. First is the cognitive challenge where programmers cannot integrate the data effectively into a mental model of correct execution, due to the scale of the state of a typical scientific application. Second, traditional control-centric debugging approach becomes unwieldy when thousands of compute threads involved. Finally, typical parallel debuggers generally don't utilize the underlying parallel platform to improve their own performance.
This research argues a more data-centric debugging approach, in which adhoc debug-time assertions can be used to test the state of a large distributed array, and can be refined iteratively to locate program’s defects. Furthermore, this research proposes a scheme that executes the assertion in parallel, making assertions over large data structures feasible.
The implementation of different types of debug-time assertions, and various case studies, along with thorough performance evaluation results have been presented in several publications.