THEANO
test_gpu.py:
# http://deeplearning.net/software/theano/tutorial/using_gpu.html#testing-theano-with-gpu
from theano import function, config, shared, tensor
import numpy
import time
vlen = 10 * 30 * 768 # 10 x #cores x # threads per core
iters = 1000
rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
f = function([], tensor.exp(x))
print(f.maker.fgraph.toposort())
t0 = time.time()
for i in range(iters):
r = f()
t1 = time.time()
print("Looping %d times took %f seconds" % (iters, t1 - t0))
print("Result is %s" % (r,))
if numpy.any([isinstance(x.op, tensor.Elemwise) and
('Gpu' not in type(x.op).__name__)
for x in f.maker.fgraph.toposort()]):
print('Used the cpu')
else:
print('Used the gpu')
PYTORCH
import torch
torch.cuda.current_device()
torch.cuda.device(0)
torch.cuda.device_count()
torch.cuda.get_device_name(0)
torch.cuda.is_available()
REFERENCE
- Theano, http://deeplearning.net/software/theano/tutorial/using_gpu.html#testing-theano-with-gpu
- Pytorch, https://stackoverflow.com/questions/48152674/how-to-check-if-pytorch-is-using-the-gpu#48152675
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