def main():
cu_discriminant = vectorize([f4(f4, f4, f4), f8(f8, f8, f8)],
target='gpu')(poly.discriminant)
N = 1e+8 // 2
print 'Data size', N
A, B, C = poly.generate_input(N, dtype=np.float32)
D = np.empty(A.shape, dtype=A.dtype)
stream = cuda.stream()
print '== One'
ts = time()
with stream.auto_synchronize():
dA = cuda.to_device(A, stream)
dB = cuda.to_device(B, stream)
dC = cuda.to_device(C, stream)
dD = cuda.to_device(D, stream, copy=False)
cu_discriminant(dA, dB, dC, out=dD, stream=stream)
dD.to_host(stream)
te = time()
total_time = (te - ts)
print 'Execution time %.4f' % total_time
print 'Throughput %.2f' % (N / total_time)
print '== Chunked'
chunksize = 1e+7
chunkcount = N // chunksize
print 'Chunk size', chunksize
sA = np.split(A, chunkcount)
sB = np.split(B, chunkcount)
sC = np.split(C, chunkcount)
sD = np.split(D, chunkcount)
device_ptrs = []
ts = time()
with stream.auto_synchronize():
for a, b, c, d in zip(sA, sB, sC, sD):
dA = cuda.to_device(a, stream)
dB = cuda.to_device(b, stream)
dC = cuda.to_device(c, stream)
dD = cuda.to_device(d, stream, copy=False)
cu_discriminant(dA, dB, dC, out=dD, stream=stream)
dD.to_host(stream)
device_ptrs.extend([dA, dB, dC, dD])
te = time()
total_time = (te - ts)
print 'Execution time %.4f' % total_time
print 'Throughput %.2f' % (N / total_time)
if '-verify' in sys.argv[1:]:
poly.check_answer(D, A, B, C)
def main():
cu_discriminant = vectorize([f4(f4, f4, f4), f8(f8, f8, f8)],
target='cuda')(poly.discriminant)
N = 1e+8 // 2
print('Data size', N)
A, B, C = poly.generate_input(N, dtype=np.float32)
D = np.empty(A.shape, dtype=A.dtype)
stream = cuda.stream()
print('== One')
ts = time()
with stream.auto_synchronize():
dA = cuda.to_device(A, stream)
dB = cuda.to_device(B, stream)
dC = cuda.to_device(C, stream)
dD = cuda.to_device(D, stream, copy=False)
cu_discriminant(dA, dB, dC, out=dD, stream=stream)
dD.to_host(stream)
te = time()
total_time = (te - ts)
print('Execution time %.4f' % total_time)
print('Throughput %.2f' % (N / total_time))
print('== Chunked')
chunksize = 1e+7
chunkcount = N // chunksize
print('Chunk size', chunksize)
sA = np.split(A, chunkcount)
sB = np.split(B, chunkcount)
sC = np.split(C, chunkcount)
sD = np.split(D, chunkcount)
device_ptrs = []
ts = time()
with stream.auto_synchronize():
for a, b, c, d in zip(sA, sB, sC, sD):
dA = cuda.to_device(a, stream)
dB = cuda.to_device(b, stream)
dC = cuda.to_device(c, stream)
dD = cuda.to_device(d, stream, copy=False)
cu_discriminant(dA, dB, dC, out=dD, stream=stream)
dD.to_host(stream)
device_ptrs.extend([dA, dB, dC, dD])
te = time()
total_time = (te - ts)
print('Execution time %.4f' % total_time)
print('Throughput %.2f' % (N / total_time))
if '-verify' in sys.argv[1:]:
poly.check_answer(D, A, B, C)