Abstract
This paper describes Ant, a debugging framework targeting MPI parallel programs. The Ant framework statically analyzes programs, marking code regions as being executed by all processes or executed by only some of the processes. The analyzed program is then instrumented with calls to an invariant violation monitoring and detection library. The analysis allows regions to be instrumented based on whether all, or less than all, processes execute the region. Ant’s instrumentation strategy allows sampled monitoring across processes in regions executed by all processes. We present a case study using Ant with C-DIDUCE (a variant of DIDUCE for C) to find violations of value invariants in parallel C/MPI programs. Ant’s instrumentation strategy reduces the overhead of monitoring by over 14 times with less impact on accuracy than a scheme that simply distributes monitoring over all processes executing the program.
This material is based upon work supported by the National Science Foundation under Grant No. CCF-0916901.
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Lee, JW., Bachega, L.R., Midkiff, S.P., Hu, Y.C. (2013). Ant: A Debugging Framework for MPI Parallel Programs. In: Kasahara, H., Kimura, K. (eds) Languages and Compilers for Parallel Computing. LCPC 2012. Lecture Notes in Computer Science, vol 7760. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37658-0_15
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DOI: https://doi.org/10.1007/978-3-642-37658-0_15
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