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. 2019 Jun 25;51:30. doi: 10.1186/s12711-019-0472-8

Table 2.

Characteristics of preconditioned (deflated) coefficient matrices, and of PCG and DPCG methods for solving ssSNPBLUP applied to the field dataset

Modela Method kO/kSb λminc λmaxc κd Ne Iterativetimef Time/iter.g Totaltimeh
MS PCG 1 3.70×10-5 1.75×103 4.74×107 10,000 44,808 4.5 46,081
MS PCG 10-1 1.18×10-5 1.77×102 1.51×107 10,000 51,768 5.2 53,550
MS PCG 10-2 4.37×10-6 1.95×101 4.45×106 6210 34,139 5.5 35,812
MS PCG 10-3 3.99×10-6 5.08 1.27×106 3825 19,043 5.0 20,866
MS PCG 10-4 1.50×10-6 5.07 3.37×106 7336 54,326 7.4 56,475
MS DPCG 1 2.86×10-5 4.77 1.67×105 748 6527 8.7 17,229
MS DPCG 10-1 1.41×10-5 4.77 3.37×105 1211 11,864 9.8 22,947
MS DPCG 10-2 9.17×10-6 4.77 5.20×105 1778 17,030 9.6 28,615
MS DPCG 10-3 7.50×10-6 4.77 6.36×105 2569 23,676 9.2 35,497
Liu PCG 1 7.38×10-6 1.43×102 1.93×107 10,000 44,122 4.4 45,083
Liu PCG 10-1 3.66×10-6 1.52×101 4.14×106 6049 31,085 5.1 32,018
Liu PCG 10-2 4.29×10-6 5.07 1.18×106 2669 13,225 5.0 13,888
Liu PCG 10-3 3.51×10-6 5.07 1.44×106 3606 20,578 5.7 21,458
Liu PCG 10-4 1.69×10-6 5.07 3.00×106 7033 33,534 4.8 34,675
Liu DPCG 1 5.40×10-6 5.31 9.85×105 2877 22,791 7.9 26,521
Liu DPCG 10-1 6.91×10-6 4.77 6.90×105 1628 14,231 8.7 18,049
Liu DPCG 10-2 5.23×10-6 4.77 9.11×105 2234 23,244 10.4 28,057
Liu DPCG 10-3 4.31×10-6 4.77 1.11×106 3106 34,950 11.3 39,603

aMS = ssSNPBLUP model proposed by Mantysaari and Stranden [7]; Liu = ssSNPBLUP model proposed by Liu et al. [5];

bParameters used for the second-level preconditioner;

cSmallest and largest eigenvalues of the preconditioned (deflated) coefficient matrix;

dCondition number of the preconditioned (deflated) coefficient matrix;

eNumber of iterations. A number of iterations equal to 10,000 means that the method failed to converge within 10,000 iterations;

fWall clock time (seconds) for the iterative process;

gAverage wall clock time (seconds) per iteration;

hWall clock time (seconds) for a complete process (including I/O operations)