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guanjihuan 2022-02-22 14:34:21 +08:00
parent 11d2720393
commit 14bee41b70
11 changed files with 35 additions and 212 deletions
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10
language_learning/2020.06.01_parallel_calculations_with_python/application_of_parallel_calculations_with_python.py
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@ -10,17 +10,21 @@ def main(parameter_array, task_index):
for parameter in parameter_array:
result = parameter*2
result_array.append(result)
time.sleep(np.random.uniform(1,10))
guan.write_one_dimensional_data(parameter_array, result_array, filename='task_index='+str(task_index))
if __name__ == '__main__':
cpus = 4
parameter_array_all = np.arange(0, 17, 1)
start_time = time.perf_counter()
process_array = []
for task_index in range(cpus):
parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, cpus, task_index)
p = Process(target=main, args=(parameter_array, task_index))
p.start()
p.join()
process_array.append(Process(target=main, args=(parameter_array, task_index)))
for process in process_array: # 运行子进程
process.start()
for process in process_array: # 等待子进程完成
process.join()
end_time = time.perf_counter()
print('运行时间=', (end_time-start_time), '\n')
f = open('result.txt', 'w')

21
language_learning/2020.06.01_parallel_calculations_with_python/parallel_calculations_with_python.py
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@ -26,14 +26,17 @@ if __name__ == '__main__':
print('并行程序')
print('Process id = %s.' % os.getpid())
start_time = time.perf_counter()
p = Process(target=run_proc, args=('job1',))
p.start()
p = Process(target=run_proc, args=('job2',))
p.start()
p = Process(target=run_proc, args=('job3',))
p.start()
p = Process(target=run_proc, args=('job4',))
p.start()
p.join() # join()方法可以等待子进程结束后再继续往下运行
p1 = Process(target=run_proc, args=('job1',))
p2 = Process(target=run_proc, args=('job2',))
p3 = Process(target=run_proc, args=('job3',))
p4 = Process(target=run_proc, args=('job4',))
p1.start()
p2.start()
p3.start()
p4.start()
p1.join() # join()方法可以等待子进程结束后再继续往下运行
p2.join() # join()方法可以等待子进程结束后再继续往下运行
p3.join() # join()方法可以等待子进程结束后再继续往下运行
p4.join() # join()方法可以等待子进程结束后再继续往下运行
end_time = time.perf_counter()
print('运行时间(s)=', (end_time-start_time))

16
language_learning/2020.06.01_parallel_calculations_with_python/parallel_calculations_with_python_using_Value.py Normal file
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@ -0,0 +1,16 @@
from multiprocessing import Process, Value
def run_proc(name, a, num): # 要执行的代码
num.value = a
if __name__ == '__main__':
num1 = Value('d', 0.0) # 共享内存
num2 = Value('d', 0.0) # 共享内存
p1 = Process(target=run_proc, args=('job1', 100, num1))
p2 = Process(target=run_proc, args=('job2', 200, num2))
p1.start()
p2.start()
p1.join()
p2.join()
print(num1.value)
print(num2.value)

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a0.txt
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@ -1,16 +0,0 @@
0.0 0.0
0.1 0.010000000000000002
0.2 0.04000000000000001
0.30000000000000004 0.09000000000000002
0.4 0.16000000000000003
0.5 0.25
0.6000000000000001 0.3600000000000001
0.7000000000000001 0.4900000000000001
0.8 0.6400000000000001
0.9 0.81
1.0 1.0
1.1 1.2100000000000002
1.2000000000000002 1.4400000000000004
1.3 1.6900000000000002
1.4000000000000001 1.9600000000000004
1.5 2.25

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a1.txt
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@ -1,16 +0,0 @@
1.6 2.5600000000000005
1.7000000000000002 2.8900000000000006
1.8 3.24
1.9000000000000001 3.6100000000000003
2.0 4.0
2.1 4.41
2.2 4.840000000000001
2.3000000000000003 5.290000000000001
2.4000000000000004 5.760000000000002
2.5 6.25
2.6 6.760000000000001
2.7 7.290000000000001
2.8000000000000003 7.840000000000002
2.9000000000000004 8.410000000000002
3.0 9.0
3.1 9.610000000000001

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a2.txt
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@ -1,16 +0,0 @@
3.2 10.240000000000002
3.3000000000000003 10.890000000000002
3.4000000000000004 11.560000000000002
3.5 12.25
3.6 12.96
3.7 13.690000000000001
3.8000000000000003 14.440000000000001
3.9000000000000004 15.210000000000003
4.0 16.0
4.1000000000000005 16.810000000000006
4.2 17.64
4.3 18.49
4.4 19.360000000000003
4.5 20.25
4.6000000000000005 21.160000000000004
4.7 22.090000000000003

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a3.txt
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@ -1,16 +0,0 @@
4.800000000000001 23.040000000000006
4.9 24.010000000000005
5.0 25.0
5.1000000000000005 26.010000000000005
5.2 27.040000000000003
5.300000000000001 28.090000000000007
5.4 29.160000000000004
5.5 30.25
5.6000000000000005 31.360000000000007
5.7 32.49
5.800000000000001 33.64000000000001
5.9 34.81
6.0 36.0
6.1000000000000005 37.21000000000001
6.2 38.440000000000005
6.300000000000001 39.69000000000001

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a4.txt
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@ -1,16 +0,0 @@
6.4 40.96000000000001
6.5 42.25
6.6000000000000005 43.56000000000001
6.7 44.89
6.800000000000001 46.24000000000001
6.9 47.61000000000001
7.0 49.0
7.1000000000000005 50.41000000000001
7.2 51.84
7.300000000000001 53.29000000000001
7.4 54.760000000000005
7.5 56.25
7.6000000000000005 57.760000000000005
7.7 59.290000000000006
7.800000000000001 60.84000000000001
7.9 62.410000000000004

16
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a5.txt
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@ -1,16 +0,0 @@
8.0 64.0
8.1 65.61
8.200000000000001 67.24000000000002
8.3 68.89000000000001
8.4 70.56
8.5 72.25
8.6 73.96
8.700000000000001 75.69000000000001
8.8 77.44000000000001
8.9 79.21000000000001
9.0 81.0
9.1 82.80999999999999
9.200000000000001 84.64000000000001
9.3 86.49000000000001
9.4 88.36000000000001
9.5 90.25

4
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/a6.txt
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@ -1,4 +0,0 @@
9.600000000000001 92.16000000000003
9.700000000000001 94.09000000000002
9.8 96.04000000000002
9.9 98.01

100
language_learning/2021.05.10_parallel_calculations_using_sh_files/results/combine.txt
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@ -1,100 +0,0 @@
0.0 0.0
0.1 0.010000000000000002
0.2 0.04000000000000001
0.30000000000000004 0.09000000000000002
0.4 0.16000000000000003
0.5 0.25
0.6000000000000001 0.3600000000000001
0.7000000000000001 0.4900000000000001
0.8 0.6400000000000001
0.9 0.81
1.0 1.0
1.1 1.2100000000000002
1.2000000000000002 1.4400000000000004
1.3 1.6900000000000002
1.4000000000000001 1.9600000000000004
1.5 2.25
1.6 2.5600000000000005
1.7000000000000002 2.8900000000000006
1.8 3.24
1.9000000000000001 3.6100000000000003
2.0 4.0
2.1 4.41
2.2 4.840000000000001
2.3000000000000003 5.290000000000001
2.4000000000000004 5.760000000000002
2.5 6.25
2.6 6.760000000000001
2.7 7.290000000000001
2.8000000000000003 7.840000000000002
2.9000000000000004 8.410000000000002
3.0 9.0
3.1 9.610000000000001
3.2 10.240000000000002
3.3000000000000003 10.890000000000002
3.4000000000000004 11.560000000000002
3.5 12.25
3.6 12.96
3.7 13.690000000000001
3.8000000000000003 14.440000000000001
3.9000000000000004 15.210000000000003
4.0 16.0
4.1000000000000005 16.810000000000006
4.2 17.64
4.3 18.49
4.4 19.360000000000003
4.5 20.25
4.6000000000000005 21.160000000000004
4.7 22.090000000000003
4.800000000000001 23.040000000000006
4.9 24.010000000000005
5.0 25.0
5.1000000000000005 26.010000000000005
5.2 27.040000000000003
5.300000000000001 28.090000000000007
5.4 29.160000000000004
5.5 30.25
5.6000000000000005 31.360000000000007
5.7 32.49
5.800000000000001 33.64000000000001
5.9 34.81
6.0 36.0
6.1000000000000005 37.21000000000001
6.2 38.440000000000005
6.300000000000001 39.69000000000001
6.4 40.96000000000001
6.5 42.25
6.6000000000000005 43.56000000000001
6.7 44.89
6.800000000000001 46.24000000000001
6.9 47.61000000000001
7.0 49.0
7.1000000000000005 50.41000000000001
7.2 51.84
7.300000000000001 53.29000000000001
7.4 54.760000000000005
7.5 56.25
7.6000000000000005 57.760000000000005
7.7 59.290000000000006
7.800000000000001 60.84000000000001
7.9 62.410000000000004
8.0 64.0
8.1 65.61
8.200000000000001 67.24000000000002
8.3 68.89000000000001
8.4 70.56
8.5 72.25
8.6 73.96
8.700000000000001 75.69000000000001
8.8 77.44000000000001
8.9 79.21000000000001
9.0 81.0
9.1 82.80999999999999
9.200000000000001 84.64000000000001
9.3 86.49000000000001
9.4 88.36000000000001
9.5 90.25
9.600000000000001 92.16000000000003
9.700000000000001 94.09000000000002
9.8 96.04000000000002
9.9 98.01