A Comparison of Parallel Profiling Tools for Programs utilizing the FFT

Brian Leu, Samar Aseeri, Benson Muite

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Performance monitoring is an important component of code optimization. Performance monitoring is also important for the beginning user, but can be difficult to configure appropriately. The overhead of the performance monitoring tools Craypat, FPMP, mpiP, Scalasca and TAU, are measured using default configurations likely to be choosen by a novice user and shown to be small when profiling Fast Fourier Transform based solvers for the Klein Gordon equation based on 2decomp&FFT and on FFTE. Performance measurements help explain that despite FFTE having a more efficient parallel algorithm, it is not always faster than 2decom&FFT because the complied single core FFT is not as fast as that in FFTW which is used in 2decomp&FFT.
Original languageEnglish (US)
Title of host publicationThe International Conference on High Performance Computing in Asia-Pacific Region Companion
PublisherACM
Pages36-45
Number of pages10
ISBN (Print)9781450383035
DOIs
StatePublished - Jan 6 2021

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