# Basic Arithmetic Operation in PyCuda

A basic functioning operation is carried out

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 License of this example: Sugeerth Murugesan,UC Davis (sugeerth@gmail.com) Date: September 2nd,2013 PyCUDA version:

```   1 #!python
2 import pycuda.driver as cuda
3 import pycuda.autoinit
4 from pycuda.compiler import SourceModule
5 import pycuda.gpuarray as gpuarray
6 import numpy as np
7
8 # Converting the list into numpy array for faster access and putting it into the GPU for processing...
9 start = cuda.Event()
10 end = cuda.Event()
11
12 N = 222341
13
14 values = np.random.randn(N)
15 number_of_blocks=N/1024
16
17 # Calculating the (value-max)/max-min computation and storing it in a numpy array. Pre-calculating the maximum and minimum values.
18
19 # Space for the Kernel computation..
20
21 func_mod = SourceModule("""
22 // Needed to avoid name mangling so that PyCUDA can
23 // find the kernel function:
24 extern "C" {
25 __global__ void func(float *a, int N, float minval, int denom)
26 {
28 if (idx < N)
29     a[idx] = (a[idx]-minval)/denom;
30 }
31 }
32 """, no_extern_c=1)
33
34 func = func_mod.get_function('func')
35 x = np.asarray(values, np.float32)
36 x_gpu = gpuarray.to_gpu(x)
37 h_minval = np.int32(0)
38 h_denom = np.int32(255)
39
40 start.record()
41 # a function to the GPU to calculate the computation in the GPU.
42 func(x_gpu.gpudata, np.uint32(N), np.uint32(h_minval), np.uint32(h_denom), block=(1024, 1, 1), grid=(number_of_blocks+1,1,1))
43 end.record()
44 end.synchronize()
45 secs = start.time_till(end)*1e-3
46
47 print "SourceModule time"
48 print "%fs" % (secs)
49 print 'x:       ', x[N-1]
50 print 'Func(x): ', x_gpu.get()[N-1],'Actual: ',(values[N-1]-0)/(h_denom)
51 x_colors=x_gpu.get()
```

PyCuda/Examples/ArithmeticExample (last edited 2014-10-22 00:48:04 by ::ffff:128)