CG Versus MINRES: An Empirical Comparison

  • Chin-Lung Fong D
  • Saunders M
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Abstract

For iterative solution of symmetric systems  the conjugate gradient method (CG) is commonly used when A is positive definite, while the minimum residual method (MINRES) is typically reserved for indefinite systems. We investigate the sequence of approximate solutions  generated by each method and suggest that even if A is positive definite, MINRES may be preferable to CG if iterations are to be terminated early. In particular, we show for MINRES that the solution norms  are monotonically increasing when A is positive definite (as was already known for CG), and the solution errors  are monotonically decreasing. We also show that the backward errors for the MINRES iterates  are monotonically decreasing.

Figures

  • Table 1. Pseudocode for algorithms CG and CR
  • Figure 2. Comparison of backward and forward errors for CG and MINRES solving two spd systems = .Ax b
  • Figure 3. Comparison of backward and forward errors for CG and MINRES solving two more spd systems = .Ax b
  • Figure 4. Comparison of residual and solution norms for CG and MINRES solving two spd systems = .Ax b
  • Figure 5. Comparison of residual and solution norms for CG and MINRES solving two more spd systems = .Ax b
  • Figure 6. For MINRES on the indefinite problem (4.2), kx and the backward error /k kr x are both slightly non-monotonic.
  • Figure 7. Residual norms and solution norms when MINRES is applied to two indefinite systems ( ) = .A I x b
  • Figure 8. Residual norms and solution norms when MINRES is applied to two more indefinite systems ( ) = .A I x b

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CITATION STYLE

APA

Chin-Lung Fong, D., & Saunders, M. (2012). CG Versus MINRES: An Empirical Comparison. Sultan Qaboos University Journal for Science [SQUJS], 16, 44. https://doi.org/10.24200/squjs.vol17iss1pp44-62

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