title: What's the effect of CNMeM enabled but 'cuDNN not available' in Theano?
body: <p>I have the following code based on <a href="http://deeplearning.net/software/theano/tutorial/using_gpu.html" rel="nofollow">Theano example</a>:</p>
  
  <pre><code>from theano import function, config, shared, sandbox
  import theano.tensor as T
  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([], T.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, T.Elemwise) for x in f.maker.fgraph.toposort()]):
      print('Used the cpu')
  else:
      print('Used the gpu')
  </code></pre>
  
  <p>Now when I test the code with two modes:</p>
  
  <p>GPU mode, I get this:</p>
  
  <pre><code>$ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python gpu.py
  Using gpu device 0: Tesla C2075 (CNMeM is enabled with initial size: 95.0% of memory, cuDNN not available)
  [GpuElemwise{exp,no_inplace}(&lt;CudaNdarrayType(float32, vector)&gt;), HostFromGpu(GpuElemwise{exp,no_inplace}.0)]
  Looping 1000 times took 0.475526 seconds
  Result is [ 1.23178029  1.61879349  1.52278066 ...,  2.20771813  2.29967761
    1.62323296]
  Used the gpu
  </code></pre>
  
  <p>CPU mode, I get this:</p>
  
  <pre><code>$ THEANO_FLAGS=mode=FAST_RUN,device=cpu,floatX=float32 python gpu.py
  [Elemwise{exp,no_inplace}(&lt;TensorType(float32, vector)&gt;)]
  Looping 1000 times took 5.221368 seconds
  Result is [ 1.23178029  1.61879337  1.52278066 ...,  2.20771813  2.29967761
    1.62323284]
  Used the cpu
  </code></pre>
  
  <p>Notice two things, GPU is indeed faster than CPU (0.47sec vs 5 sec). But at the same time at GPU I get the cuDNN not available message.</p>
  
  <p>My question is this. What's the effect of the absence of cuDNN? Is it harmful?</p>