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Table 2 Comparison of run times of FFVA and VFFVA in small models in seconds. The results are presented as the mean and standard deviation of five runs

From: VFFVA: dynamic load balancing enables large-scale flux variability analysis

Model FFVA mean(std) loading and analysis time VFFVA mean(std) loading and analysis time FFVA mean(std) analysis only
2 cores
Ecoli_core 19.5(0.5) 0.2(0.01) 0.37(0.1)
P_putida 19.2(0.7) 0.6(0.02) 0.81(0.09)
EcoliK12 20.4(0.6) 2.2(0.06) 2.41(0.09)
4 cores
Ecoli_core 19.6(0.6) 0.2(0.005) 0.32(0.01)
P_putida 19.4(1) 0.5(0.02) 0.61(0.01)
EcoliK12 20(0.8) 1.3(0.04) 1.64(0.08)
8 cores
Ecoli_core 19.4(0.5) 0.2(0.03) 0.35(0.05)
P_putida 19.6(0.7) 0.4(0.04) 0.53(0.009)
EcoliK12 20(0.49) 0.9(0.01) 1.22(0.08)
16 cores
Ecoli_core 20.2(0.4) 0.2(0.008) 0.41(0.05)
P_putida 19.5(0.4) 0.4(0.04) 0.51(0.03)
EcoliK12 22(0.7) 0.7(0.01) 0.87(0.03)
32 cores
Ecoli_core 22.2(0.4) 0.3(0.008) 0.6(0.12)
P_putida 21.5(0.6) 0.4(0.01) 0.53(0.004)
EcoliK12 21.5(0.6) 0.6(0.03) 0.78(0.04)