Abstract
This article describes how the integration of the OpenUH OpenMP compiler with the KOJAK performance analysis tool can assist developers of OpenMP and hybrid codes in optimizing their applications with as little user intervention as possible. In particular, we (i) describe how the compiler’s ability to automatically instrument user code down to the flow-graph level can improve the location of performance problems and (ii) outline how the performance feedback provided by KOJAK will direct the compiler’s optimization decisions in the future. To demonstrate our methodology, we present experimental results showing how reasons for the performance slow down of the ASPCG benchmark could be identified.
This material is based upon work supported by the National Science Foundation under grant No. 0444363 and 0444468.
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Hernandez, O. et al. (2008). Performance Instrumentation and Compiler Optimizations for MPI/OpenMP Applications. In: Mueller, M.S., Chapman, B.M., de Supinski, B.R., Malony, A.D., Voss, M. (eds) OpenMP Shared Memory Parallel Programming. IWOMP 2005. Lecture Notes in Computer Science, vol 4315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68555-5_22
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