Optimization of the oktay-kronfeld action conjugate gradient inverter

Yong Chull Jang, Jon A. Bailey, Weonjong Lee, Carleton Detar, Mehmet B. Oktay, Andreas S. Kronfeld

Research output: Contribution to journalConference articlepeer-review


Improving the Fermilab action to third order in heavy quark effective theory yields the Oktay- Kronfeld action, a promising candidate for precise calculations of the spectra of heavy quark systems and weak matrix elements relevant to searches for new physics. We have optimized the bi-stabilized conjugate gradient inverter in the SciDAC QOPQDP library and are developing a GPU code. The action is rewritten and the needed gauge-link combinations are precalculated. In tests with a MILC coarse lattice, this procedure accelerates the inverter by a factor of four. The remaining floating-point operations are mostly simple matrix multiplications between gauge links and fermion vectors, which we accelerate by more than an order of magnitude by using CUDA. Further gains could be achieved by using QUDA.

Original languageEnglish
Article number030
JournalProceedings of Science
Publication statusPublished - 2013
Event31st International Symposium on Lattice Field Theory, LATTICE 2013 - Mainz, Germany
Duration: 2013 Jul 292013 Aug 3

Bibliographical note

Funding Information:
This work was supported in part by the U.S. Department of Energy under grant No. DE-FC0212ER-41879 (C.D.) and the U.S. National Science Foundation under grant PHY10-67881 (C.D.). The research of W. Lee is supported by the Creative Research Initiatives Program (2013-003454) of the NRF grant funded by the Korean government (MSIP). W. Lee would like to acknowledge the support from KISTI supercomputing center through the strategic support program for the supercomputing application research [No. KSC-2012-G3-08]. Computations were carried out on the DAVID GPU clusters at Seoul National University. The research of J.A.B. is supported by the Basic Science Research Program (2013009149) of the National Research Foundation of Korea (NRF) funded by the Ministry of Education.

All Science Journal Classification (ASJC) codes

  • General


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