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Keywords: event-based debugging, Ariadne, parallel, scalable
Massively parallel computations are difficult to debug. Users are often overwhelmed by large amounts of trace data and confused by the effects of asynchrony. Event-based behavioral abstraction provides a mechanism for managing the volume of data by allowing users to specify models of intended program behavior that are automatically compared to actual program behavior. Transformations of logical time ameliorate the difficulties of coping with asynchrony by allowing users to see behavior from a variety of temporal perspectives. Previously, we combined these features in a debugger that automatically constructed animations of user-defined abstract events in logical time. However, our debugger, like many others, did not always provide sufficient feedback nor did it effectively scale up for massive parallelism. Our modeling language required complex recognition algorithms which precluded informative feedback on abstractions that did not correspond to observed behavior. Feedback on abstractions that did match behavior was limited because it relied on graphical animations that did not scale well to even moderate numbers of processes (such as 64). We address these problems in a new debugger, called Ariadne.
Created: Fri Dec 3 12:16:26 1999
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