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 = 320000000
 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_time = timer() - start
 print("c[:5] = " + str(C[:5]))
 print("c[-5:] = " + str(C[-5:]))
 print("vectorAdd took %f seconds " % vectorAdd_time)
if name == 'main':
 main()

import pycuda.autoinit
import pycuda.driver as drv
import numpy as np
from timeit import default_timer as timer
from pycuda.compiler import SourceModule
mod = SourceModule("""
global void func(float *a, float *b, size_t N)
{
 const int i = blockIdx.x * blockDim.x + threadIdx.x;
 if (i >= N)
 {
 return;
 }
 float temp_a = a[i];
 float temp_b = b[i];
 a[i] = (temp_a * 10 + 2 ) * ((temp_b + 2) * 10 - 5 ) * 5;
 // a[i] = a[i] + b[i];
}
""")
func = mod.get_function("func") 
def test(N):
 # N = 1024 * 1024 * 90 # float: 4M = 1024 * 1024
 print("N = %d" % N)
 N = np.int32(N)
 a = np.random.randn(N).astype(np.float32)
 b = np.random.randn(N).astype(np.float32) 
 # copy a to aa
 aa = np.empty_like(a)
 aa[:] = a
 # GPU run
 nTheads = 256
 nBlocks = int( ( N + nTheads - 1 ) / nTheads )
 start = timer()
 func(
 drv.InOut(a), drv.In(b), N,
 block=( nTheads, 1, 1 ), grid=( nBlocks, 1 ) )
 run_time = timer() - start 
 print("gpu run time %f seconds " % run_time) 
 # cpu run
 start = timer()
 aa = (aa * 10 + 2 ) * ((b + 2) * 10 - 5 ) * 5
 run_time = timer() - start 
 print("cpu run time %f seconds " % run_time) 
 # check result
 r = a - aa
 print( min(r), max(r) )
def main():
 for n in range(1, 10):
 N = 1024 * 1024 * (n * 10)
 print("------------%d---------------" % n)
 test(N)
if name == 'main':
 main()