C:\test>mpiexec -np 2 "C:\ProgramData\Anaconda3\python.exe" ex01.py
gaft.ConsoleOutputAnalysis INFO Generation: 0, best fitness: 19.883
gaft.ConsoleOutputAnalysis INFO Generation: 0, best fitness: 24.853
gaft.ConsoleOutputAnalysis INFO Generation: 1, best fitness: 19.883
gaft.ConsoleOutputAnalysis INFO Generation: 1, best fitness: 24.854
gaft.ConsoleOutputAnalysis INFO Generation: 2, best fitness: 19.883
gaft.ConsoleOutputAnalysis INFO Generation: 2, best fitness: 24.854
gaft.ConsoleOutputAnalysis INFO Generation: 3, best fitness: 19.883
gaft.ConsoleOutputAnalysis INFO Generation: 3, best fitness: 24.854
gaft.ConsoleOutputAnalysis INFO Generation: 4, best fitness: 20.600
gaft.ConsoleOutputAnalysis INFO Generation: 4, best fitness: 24.854
gaft.ConsoleOutputAnalysis INFO Generation: 5, best fitness: 20.600
gaft.ConsoleOutputAnalysis INFO Generation: 5, best fitness: 24.854
gaft.ConsoleOutputAnalysis INFO Generation: 6, best fitness: 20.600
gaft.ConsoleOutputAnalysis INFO Generation: 6, best fitness: 24.855
gaft.ConsoleOutputAnalysis INFO Generation: 7, best fitness: 20.677
gaft.ConsoleOutputAnalysis INFO Generation: 7, best fitness: 24.855
gaft.ConsoleOutputAnalysis INFO Generation: 8, best fitness: 20.677
gaft.ConsoleOutputAnalysis INFO Generation: 9, best fitness: 20.677
gaft.ConsoleOutputAnalysis INFO Generation: 8, best fitness: 24.855
gaft.FitnessStore INFO Best fitness values are written to best_fit.py
gaft.ConsoleOutputAnalysis INFO Optimal solution: ([9.3212890625], 20.6766
55455888568)
gaft.ConsoleOutputAnalysis INFO Generation: 9, best fitness: 24.855
gaft.FitnessStore INFO Best fitness values are written to best_fit.py
gaft.ConsoleOutputAnalysis INFO Optimal solution: ([7.855224609375], 24.85
494496737466)
hoboly
commented
5 years ago
請問為什麼我的電腦會運行 2 組? 而不是1組data 分派給2個核心?
C:\test>mpiexec -np 2 "C:\ProgramData\Anaconda3\python.exe" ex01.py gaft.ConsoleOutputAnalysis INFO Generation: 0, best fitness: 19.883 gaft.ConsoleOutputAnalysis INFO Generation: 0, best fitness: 24.853 gaft.ConsoleOutputAnalysis INFO Generation: 1, best fitness: 19.883 gaft.ConsoleOutputAnalysis INFO Generation: 1, best fitness: 24.854 gaft.ConsoleOutputAnalysis INFO Generation: 2, best fitness: 19.883 gaft.ConsoleOutputAnalysis INFO Generation: 2, best fitness: 24.854 gaft.ConsoleOutputAnalysis INFO Generation: 3, best fitness: 19.883 gaft.ConsoleOutputAnalysis INFO Generation: 3, best fitness: 24.854 gaft.ConsoleOutputAnalysis INFO Generation: 4, best fitness: 20.600 gaft.ConsoleOutputAnalysis INFO Generation: 4, best fitness: 24.854 gaft.ConsoleOutputAnalysis INFO Generation: 5, best fitness: 20.600 gaft.ConsoleOutputAnalysis INFO Generation: 5, best fitness: 24.854 gaft.ConsoleOutputAnalysis INFO Generation: 6, best fitness: 20.600 gaft.ConsoleOutputAnalysis INFO Generation: 6, best fitness: 24.855 gaft.ConsoleOutputAnalysis INFO Generation: 7, best fitness: 20.677 gaft.ConsoleOutputAnalysis INFO Generation: 7, best fitness: 24.855 gaft.ConsoleOutputAnalysis INFO Generation: 8, best fitness: 20.677 gaft.ConsoleOutputAnalysis INFO Generation: 9, best fitness: 20.677 gaft.ConsoleOutputAnalysis INFO Generation: 8, best fitness: 24.855 gaft.FitnessStore INFO Best fitness values are written to best_fit.py gaft.ConsoleOutputAnalysis INFO Optimal solution: ([9.3212890625], 20.6766 55455888568) gaft.ConsoleOutputAnalysis INFO Generation: 9, best fitness: 24.855 gaft.FitnessStore INFO Best fitness values are written to best_fit.py gaft.ConsoleOutputAnalysis INFO Optimal solution: ([7.855224609375], 24.85 494496737466)