title: Tensorflow: Cuda compute capability 3.0. The minimum required Cuda capability is 3.5
body: <p>I am installing tensorflow from source <a href="https://www.tensorflow.org/versions/r0.10/get_started/os_setup.html#installing-from-sources" rel="noreferrer">(documentation)</a>. </p>
  
  <p>Cuda driver version:</p>
  
  <pre><code>nvcc: NVIDIA (R) Cuda compiler driver
  Cuda compilation tools, release 7.5, V7.5.17
  </code></pre>
  
  <p>When I ran the following command :</p>
  
  <pre><code>bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
  </code></pre>
  
  <p>it gave me the following error :</p>
  
  <pre><code>I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally
  I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
  I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally
  I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so.1 locally
  I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally
  I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:925] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
  I tensorflow/core/common_runtime/gpu/gpu_init.cc:118] Found device 0 with properties: 
  name: GeForce GT 640
  major: 3 minor: 0 memoryClockRate (GHz) 0.9015
  pciBusID 0000:05:00.0
  Total memory: 2.00GiB
  Free memory: 1.98GiB
  I tensorflow/core/common_runtime/gpu/gpu_init.cc:138] DMA: 0 
  I tensorflow/core/common_runtime/gpu/gpu_init.cc:148] 0:   Y 
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  I tensorflow/core/common_runtime/gpu/gpu_device.cc:843] Ignoring gpu device (device: 0, name: GeForce GT 640, pci bus id: 0000:05:00.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5.
  F tensorflow/cc/tutorials/example_trainer.cc:128] Check failed: ::tensorflow::Status::OK() == (session-&gt;Run({{"x", x}}, {"y:0", "y_normalized:0"}, {}, &amp;outputs)) (OK vs. Invalid argument: Cannot assign a device to node 'Cast': Could not satisfy explicit device specification '/gpu:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
       [[Node: Cast = Cast[DstT=DT_FLOAT, SrcT=DT_INT32, _device="/gpu:0"](Const)]])
  F tensorflow/cc/tutorials/example_trainer.cc:128] Check failed: ::tensorflow::Status::OK() == (session-&gt;Run({{"x", x}}, {"y:0", "y_normalized:0"}, {}, &amp;outputs)) (OK vs. Invalid argument: Cannot assign a device to node 'Cast': Could not satisfy explicit device specification '/gpu:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
       [[Node: Cast = Cast[DstT=DT_FLOAT, SrcT=DT_INT32, _device="/gpu:0"](Const)]])
  F tensorflow/cc/tutorials/example_trainer.cc:128] Check failed: ::tensorflow::Status::OK() == (session-&gt;Run({{"x", x}}, {"y:0", "y_normalized:0"}, {}, &amp;outputs)) (OK vs. Invalid argument: Cannot assign a device to node 'Cast': Could not satisfy explicit device specification '/gpu:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
       [[Node: Cast = Cast[DstT=DT_FLOAT, SrcT=DT_INT32, _device="/gpu:0"](Const)]])
  F tensorflow/cc/tutorials/example_trainer.cc:128] Check failed: ::tensorflow::Status::OK() == (session-&gt;Run({{"x", x}}, {"y:0", "y_normalized:0"}, {}, &amp;outputs)) (OK vs. Invalid argument: Cannot assign a device to node 'Cast': Could not satisfy explicit device specification '/gpu:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
       [[Node: Cast = Cast[DstT=DT_FLOAT, SrcT=DT_INT32, _device="/gpu:0"](Const)]])
  Aborted (core dumped)
  </code></pre>
  
  <p>Will I need a different gpu to run this?</p>