title: Can TensorFlow run with multiple CPUs (no GPUs)?
body: <p>I'm trying to learn distributed TensorFlow. Tried out a piece code as explained <a href="https://www.youtube.com/watch?v=la_M6bCV91M" rel="noreferrer">here</a>:</p>
  
  <pre><code>with tf.device("/cpu:0"):
      W = tf.Variable(tf.zeros([784, 10]))
      b = tf.Variable(tf.zeros([10]))
  
  with tf.device("/cpu:1"):
      y = tf.nn.softmax(tf.matmul(x, W) + b)
      loss = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
  </code></pre>
  
  <p><strong>Getting the following error:</strong></p>
  
  <pre>tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation 'MatMul': Operation was explicitly assigned to /device:CPU:1 but available devices are [ /job:localhost/replica:0/task:0/cpu:0 ]. Make sure the device specification refers to a valid device.
       [[Node: MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/device:CPU:1"](Placeholder, Variable/read)]]</pre>
  
  <p>Meaning that TensorFlow does not recognize <strong>CPU:1</strong>.</p>
  
  <p>I'm running on a RedHat server with 40 CPUs (<code>cat /proc/cpuinfo | grep processor | wc -l</code>).</p>
  
  <p>Any ideas?</p>