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MILC staggered conjugate gradient performance on Intel KNL

Conference · · Proceedings of Science (POS)
OSTI ID:1398438
 [1];  [2];  [3];  [1];  [4];  [5];  [6]
  1. Indiana Univ., Bloomington, IN (United States). Dept. of Physics
  2. Univ. of Utah, Salt Lake City, UT (United States). Dept. of Physics and Astronomy
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
  4. Intel Corp., Hillsboro, OR (United States). Sofware and Services Group
  5. Intel Labs., Bangalore (India). Parallel Computing Lab.
  6. Univ. of Arizona, Tucson, AZ (United States). Physics Dept.
+ Show Author Affiliations

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 gener- ation 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.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
AC02-05CH11231
OSTI ID:
1398438
Journal Information:
Proceedings of Science (POS), Journal Name: Proceedings of Science (POS)
Country of Publication:
United States
Language:
English

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97 MATHEMATICS AND COMPUTING