title: Titan X Pascal on VGG16 much slower on my machine than in benchmark
body: <p>I have a Titan X Pascal, Intel i5-6600, 16GB Ram and running torch7 in Ubuntu 14.04. The Nvidia driver version is 375.20, CUDA Toolkit 8.0 and cuDNN v5.1.</p>
  
  <p>I did the same test with the same VGG16 network from Caffe (imported via loadcaffe) as <a href="https://github.com/jcjohnson/cnn-benchmarks" rel="nofollow noreferrer">in this Benchmark</a>. However, for a forward pass my setup needs 80ms which is double the time as it apparently needs in the benchmark.</p>
  
  <p>I also generated a batch of 16 images with 3 channels and size 224x224. The relevant code is:</p>
  
  <pre><code> local model = loadcaffe.load("/home/.../Models/VGG16/VGG_ILSVRC_16_layers_deploy.prototxt",
                            "/home/.../Models/VGG16/VGG_ILSVRC_16_layers.caffemodel",
                            "cudnn")
  
   for i=1, 50 do
     local input = torch.randn(16, 3, 224, 224):type("torch.CudaTensor")
  
     cutorch.synchronize()
     local timer = torch.Timer()
  
     model:forward(input)
     cutorch.synchronize()
  
     local deltaT = timer:time().real
     print("Forward time: " .. deltaT)
   end
  </code></pre>
  
  <p>The output is:
  <code>
  Forward time: 0.96536016464233
  Forward time: 0.10063600540161
  Forward time: 0.096444129943848
  Forward time: 0.089151859283447
  Forward time: 0.082037925720215
  Forward time: 0.082045078277588
  Forward time: 0.079913139343262
  Forward time: 0.080273866653442
  Forward time: 0.080694913864136
  Forward time: 0.082727193832397
  Forward time: 0.082070827484131
  Forward time: 0.079407930374146
  Forward time: 0.080456018447876
  Forward time: 0.083559989929199
  Forward time: 0.082060098648071
  Forward time: 0.081624984741211
  Forward time: 0.080413103103638
  Forward time: 0.083755016326904
  Forward time: 0.083209037780762
  ...
  </code></p>
  
  <p>Do I have to do anything additional to get that speed? Or am I doing something wrong here?
  Or is it maybe because I am using Ubuntu 14.04, instead of Ubuntu 16.04 (although in the benchmark a GTX 1080 running on Ubuntu 14.04 also only needs 60ms)?</p>