Speaker
Dr
Ruizi Li
(Indiana University)
Description
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.
Primary author
Dr
Ruizi Li
(Indiana University)
Co-authors
Mr
Ashish Jha
(Intel)
Dr
Balint Joo
(Jefferson Lab)
Prof.
Carleton DeTar
(University of Utah)
Mr
Dhiraj Kalamkar
(Intel)
Prof.
Doug Toussaint
(University of Arizona)
Dr
Douglas Doerfler
(Lawrence Berkeley National Laboratory)
Prof.
Steven Gottlieb
(Indiana University)
