Question

我运行了我在CUDA Python简介页面上阅读的代码： -

import numpy as np
from timeit import default_timer as timer
from numbapro import vectorize

@vectorize(["float32(float32, float32)"], target='gpu')
def VectorAdd(a, b):
        return a + b

def main():
    N = 32000000

    A = np.ones(N, dtype=np.float32)
    B = np.ones(N, dtype=np.float32)
    C = np.zeros(N, dtype=np.float32)

    start = timer()
    C = VectorAdd(A, B)
    vectoradd_timer = timer() - start

    print("C[:5] = " + str(C[:5]))
    print("C[-5:] = " + str(C[-5:]))

    print("VectorAdd took %f seconds" % vectoradd_timer)

if __name__ == '__main__':
    main()

我在终端上收到以下错误： -

dtn34@dtn34-ubuntu:~/Python$ python asd.py
Traceback (most recent call last):
  File "asd.py", line 3, in <module>
    from numbapro import vectorize
ImportError: No module named numbapro

它应该使用gpu运行代码，但我收到了这个错误。我已经安装了anaconda，更新了conda，使用conda安装加速，安装了cudatoolkit，使用conda安装了numba。我尝试使用python2和python3

进行编译

我该怎么办？

Answer 1

知道了。正如WarrenWeckesser和Robert Crovella所指出的那样，NumbaPro已被弃用，所有功能都转移到了numba。因此，你应该写numba

而不是numbapro

from numba import vectorize

此外，目标需要设置为＆＃39; cuda＆＃39;而不是＆＃39; gpu＆＃39;

@vectorize(["float32(float32, float32)"], target='cuda')
def VectorAdd(a, b):
        return a + b

Answer 2

修改后，我试图同时在CPU和GPU中运行它，CPU的速度比GPU快

CPU中的第一个：

import numpy as np
from timeit import  default_timer as timer
# from numba import vectorize
# @vectorize(["float32(float32, float32)"], target='cuda')

def VectorAdd(a ,b):
    return a + b

def main():
    N = 32000000
    A = np.ones(N, dtype=np.float32)
    B = np.ones(N, dtype=np.float32)
    C = np.ones(N, dtype=np.float32)

    srart = timer()
    C = VectorAdd(A,B)
    vectoradd_time = timer() - srart
    print ("C[:5] = " + str(C[:5]))
    print ("C[:-5] = " + str(C[:-5]))
    print ('vectoradd_time %f second' % vectoradd_time)
if __name__== '__main__':
    main()

时间：

vectoradd_time 0.046457 second

GPU中的第二个：

import numpy as np
from timeit import default_timer as timer
from numba import vectorize

@vectorize(["float32(float32, float32)"], target='cuda')


def VectorAdd(a, b):
        return a + b

def main():
    N = 32000000

    A = np.ones(N, dtype=np.float32)
    B = np.ones(N, dtype=np.float32)
    C = np.zeros(N, dtype=np.float32)

    start = timer()
    C = VectorAdd(A, B)
    vectoradd_timer = timer() - start

    print("C[:5] = " + str(C[:5]))
    print("C[-5:] = " + str(C[-5:]))

    print("VectorAdd took %f seconds" % vectoradd_timer)

if __name__ == '__main__':
    main()

时间：

VectorAdd took 0.240731 seconds

此结果取决于您的CPU规格。

没有名为numbapro的模块

2 个答案: