TY - JOUR
T1 - Communication-hiding pipelined BiCGSafe methods for solving large linear systems
AU - Huynh, Viet Q.H.
AU - Suito, Hiroshi
N1 - Funding Information:
The authors would like to acknowledge the reviewer for the helpful suggestions that helped improve the manuscript. The lead author would like to thank Professor Emeritus Seiji Fujino at Kyushu University for the useful comments on the research. This work was supported by JST CREST Grant Number JPMJCR15D1, Japan. Numerical simulations were partially carried out on the supercomputer system AFI-NITY at the Advanced Fluid Information Research Center, Institute of Fluid Science, Tohoku University.
Publisher Copyright:
© 2023
PY - 2023
Y1 - 2023
N2 - Recently, a new variant of the BiCGStab method, known as the pipelined BiCGStab, has been proposed. This method can achieve a higher degree of scalability and speed-up rates through a mechanism in which the communication phase for the computation of the inner product can be overlapped with the computation of the matrix-vector product. Meanwhile, several generalized iteration methods with better convergence behavior than BiCGStab exist, such as ssBiCGSafe, BiCGSafe, and GPBi-CG. Among these methods, ssBiCGSafe, which requires a single phase of computing inner products per iteration, is best suited for high-performance computing systems. As described herein, inspired by the success of the pipelined BiCGStab method, we propose pipelined variations of the ssBiCGSafe method in which only one phase of inner product computation per iteration is required and this phase of inner product computation can be overlapped with the matrix-vector computation. Through numerical experimentation, we demonstrate that the proposed methods engender improvements in convergence behavior and execution time compared to the pipelined BiCGStab and ssBiCGSafe methods.
AB - Recently, a new variant of the BiCGStab method, known as the pipelined BiCGStab, has been proposed. This method can achieve a higher degree of scalability and speed-up rates through a mechanism in which the communication phase for the computation of the inner product can be overlapped with the computation of the matrix-vector product. Meanwhile, several generalized iteration methods with better convergence behavior than BiCGStab exist, such as ssBiCGSafe, BiCGSafe, and GPBi-CG. Among these methods, ssBiCGSafe, which requires a single phase of computing inner products per iteration, is best suited for high-performance computing systems. As described herein, inspired by the success of the pipelined BiCGStab method, we propose pipelined variations of the ssBiCGSafe method in which only one phase of inner product computation per iteration is required and this phase of inner product computation can be overlapped with the matrix-vector computation. Through numerical experimentation, we demonstrate that the proposed methods engender improvements in convergence behavior and execution time compared to the pipelined BiCGStab and ssBiCGSafe methods.
KW - BiCGSafe methods
KW - Global reduction
KW - GPBi-CG methods
KW - Krylov subspace methods
KW - Latency hiding
KW - Parallellization
KW - Pipelined BiCGStab methods
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U2 - 10.1016/j.amc.2023.127868
DO - 10.1016/j.amc.2023.127868
M3 - Article
AN - SCOPUS:85148336291
SN - 0096-3003
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
M1 - 127868
ER -