Does Google Cloud ML support GPU?

Question

I'm testing Google Cloud ML for speeding up my ML model using Tensorflow.

Unfortunately, it seems like Google Cloud ML is extremely slow. My Mainstream-Level PC is at least 10x faster than Google Cloud ML.

I doubt it uses GPU, so I did a test. I modified a sample code to force using GPU.

diff --git a/mnist/trainable/trainer/task.py b/mnist/trainable/trainer/task.py
index 9acb349..a64a11d 100644
--- a/mnist/trainable/trainer/task.py
+++ b/mnist/trainable/trainer/task.py
@@ -131,11 +131,12 @@ def run_training():
     images_placeholder, labels_placeholder = placeholder_inputs(
     FLAGS.batch_size)

-    # Build a Graph that computes predictions from the inference model.
-    logits = mnist.inference(images_placeholder, FLAGS.hidden1, FLAGS.hidden2)
+    with tf.device("/gpu:0"):
+      # Build a Graph that computes predictions from the inference model.
+      logits = mnist.inference(images_placeholder, FLAGS.hidden1, FLAGS.hidden2)

-    # Add to the Graph the Ops for loss calculation.
-    loss = mnist.loss(logits, labels_placeholder)
+      # Add to the Graph the Ops for loss calculation.
+      loss = mnist.loss(logits, labels_placeholder)

     # Add to the Graph the Ops that calculate and apply gradients.
     train_op = mnist.training(loss, FLAGS.learning_rate)

This training code works at my PC (gcloud beta ml local train ...) but not in cloud. It gives errors like this:

 "Traceback (most recent call last):
  File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/root/.local/lib/python2.7/site-packages/trainer/task.py", line 239, in <module>
    tf.app.run()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 43, in run
    sys.exit(main(sys.argv[:1] + flags_passthrough))
  File "/root/.local/lib/python2.7/site-packages/trainer/task.py", line 235, in main
    run_training()
  File "/root/.local/lib/python2.7/site-packages/trainer/task.py", line 177, in run_training
    sess.run(init)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1034, in _do_call
    raise type(e)(node_def, op, message)
InvalidArgumentError: Cannot assign a device to node 'softmax_linear/biases': Could not satisfy explicit device specification '/device:GPU:0' because no devices matching that specification are registered in this process; available devices: /job:localhost/replica:0/task:0/cpu:0
Colocation Debug Info:
Colocation group had the following types and devices:
ApplyGradientDescent: CPU
Identity: CPU
Assign: CPU
Variable: CPU
     [[Node: softmax_linear/biases = Variable[container="", dtype=DT_FLOAT, shape=[10], shared_name="", _device="/device:GPU:0"]()]]

Does Google Cloud ML support GPU?

Jeremy Lewi Jeremy Lewi · Accepted Answer · 2017-02-02T16:47:13

GPUs are now in Beta and all Cloud ML customers have access.

Here are the docs for using GPUs with Cloud ML.

Does Google Cloud ML support GPU?

1 Answers