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.
CITATION STYLE
Hernandez, O., Song, F., Chapman, B., Dongarra, J., Mohr, B., Moore, S., & Wolf, F. (2008). OpenMP Shared Memory Parallel Programming (Vol. 4315, pp. 267–278). Retrieved from http://www.springerlink.com/index/10.1007/978-3-540-68555-5
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