MILC staggered conjugate gradient performance on Intel KNL

Ruizi Li, Carleton DeTar, Douglas Doerfler, Steven Gottlieb, Ashish Jha, Dhiraj Kalamkar, William D Toussaint

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second generation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. We compare performance of an MPI+OpenMP baseline version of the MILC code with a version incorporating the QPhiX staggered CG solver, for both one-node and multi-node runs.

Original languageEnglish (US)
JournalProceedings of Science
VolumePart F128557
StatePublished - 2016

ASJC Scopus subject areas

  • General

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    Li, R., DeTar, C., Doerfler, D., Gottlieb, S., Jha, A., Kalamkar, D., & Toussaint, W. D. (2016). MILC staggered conjugate gradient performance on Intel KNL. Proceedings of Science, Part F128557.