mirror of
https://github.com/PacktPublishing/Hands-On-GPU-Programming-with-CUDA-C-and-Python-3.x-Second-Edition.git
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27 lines
596 B
Python
27 lines
596 B
Python
import numpy as np
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import pycuda.autoinit
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from pycuda import gpuarray
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from time import time
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host_data = np.float32( np.random.random(50000000) )
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t1 = time()
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host_data_2x = host_data * np.float32(2)
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t2 = time()
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print('total time to compute on CPU: %f' % (t2 - t1))
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device_data = gpuarray.to_gpu(host_data)
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t1 = time()
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device_data_2x = device_data * np.float32( 2 )
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t2 = time()
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from_device = device_data_2x.get()
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print('total time to compute on GPU: %f' % (t2 - t1))
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print('Is the host computation the same as the GPU computation? : {}'.format(np.allclose(from_device, host_data_2x) ))
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