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Table 3 Characteristics of preconditioned (deflated) coefficient matrices, and of PCG and DPCG methods for the reduced dataset

From: Deflated preconditioned conjugate gradient method for solving single-step BLUP models efficiently

Model Methoda Smallest eigenvalue Largest eigenvalue Effective condition number Number of iterations Total timeb Time/iterationc
ssGBLUP PCG 1.1 × 10−4 11.9 1.1 × 105 270 11.3 0.05
ssSNPBLUP PCG 1.1 × 10−4 181.0 1.7 × 106 1475 688.2 0.46
DPCG (200) 1.1 × 10−4 99.4 9.3 × 105 1221 570.5 0.47
DPCG (50) 1.1 × 10−4 40.5 3.8 × 105 890 437.7 0.49
DPCG (5) 1.1 × 10−4 6.4 6.0 × 104 331 170.1 0.49
DPCG (1) 1.1 × 10−4 6.0 5.9 × 104 270 189.6 0.66
  1. aNumber of SNP effects per subdomain is within brackets
  2. bWall clock time (s) for the iterative process
  3. cAverage wall clock time (s) per iteration. Iterations computing the residual from the coefficient matrix for the PCG method were removed before averaging
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Genetics Selection Evolution

ISSN: 1297-9686