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 language | English (US) |
|---|---|
| Title of host publication | The International Conference on High Performance Computing in Asia-Pacific Region Companion |
| Publisher | ACM |
| Pages | 36-45 |
| Number of pages | 10 |
| ISBN (Print) | 9781450383035 |
| DOIs | |
| State | Published - Jan 6 2021 |
Bibliographical note
KAUST Repository Item: Exported on 2021-02-25Acknowledgements: We thank José Gracia, Chirstoph Niethammer, Sameer Shende, Daisuke Takahashi and Brian Wylie for helpful discussions. B.L.’s work was primarily done while affiliated with the University of Michigan. B.K.M. was partially supported by HPC Europa 3 (INFRAIA-2016-1-730897) and the Estonian Center for Excellence in IT (TK148),and his work was mostly done while affiliated with the Institute of Computer Science at the University of Tartu. The computational resources used to build and test the programs were:
•Shaheen and Shaheen II operated by the KAUST Supercomputing Laboratory
•Hazelhen at HLRS.
•K computer that was operated by RIKEN.
•Rocket and Vedur operated by the University of Tartu HPCcenter.
•Mira that was operated by the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.