Publication Date:
2019-07-18
Description:
Many performance monitoring tools are currently available to the super-computing community. The performance data gathered and analyzed by these tools fall under two categories: statistics and event traces. Statistical data is much more compact but lack the probative power event traces offer. Event traces, on the other hand, can easily fill up the entire file system during execution such that the instrumented execution have to be terminated. In this paper, we propose an innovative methodology for monitoring and trace representation that offers a middle ground. The user can trace-off trace data size vs. quality incrementally. Specifically, the user will be able to limit the amount of trace collected and, at the same time, carry out some of the analysis event traces offer for the entire execution. With the help of a few CFD examples, we illustrate the use of our technique in performance tuning. We also compare quantitatively, the quality of the traces we collected vs. event traces.
Keywords:
Computer Systems
Type:
1st SIGMETRICS Symposium on Parallel and Distributed Tools; May 22, 1996 - May 23, 1996; Philadelphia, PA; United States
Format:
text
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