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How Can I Tell If H2O 3.11.0.266 Is Running With GPUs?

I've installed H2O 3.11.0.266 on a Ubuntu 16.04 with CUDA 8.0 and libcudnn.so.5.1.10 so I believe H2O should be able to find my GPUs. However, when I start up my h2o.init() in Pyth

Solution 1:

You will need the GPU-enabled version of H2O, available on the H2O download page. It is not clear from your question if you are using regular H2O or GPU-enabled H2O, however if you are using GPU-enabled H2O and have the proper dependencies, it should see your GPUs. The current dependency list is:

  • Ubuntu 16.04
  • CUDA 8.0
  • cuDNN 5.1

I have opened a JIRA ticket to add some metadata in the h2o.init() printout so that you'll see information about your GPUs there (in a future release).


Solution 2:

From a terminal window, run the nvidia-smi tool. Look at the utilization. If it's 0%, you're not using the GPUs.

In the example below, you can see Volatile GPU Utilization is 0%, so the GPUs are not being used.

$ nvidia-smi
Tue May 30 13:50:11 2017   
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 370.28                 Driver Version: 370.28                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1080    Off  | 0000:02:00.0     Off |                  N/A |
| 27%   30C    P8    10W / 180W |      1MiB /  8113MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 1080    Off  | 0000:03:00.0      On |                  N/A |
| 27%   31C    P8     9W / 180W |     38MiB /  8112MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|    1      1599    G   /usr/lib/xorg/Xorg                              36MiB |
+-----------------------------------------------------------------------------+

I use the following handy little script to monitor GPU utilization for myself.

$ cat bin/gputop 
#!/bin/bash

watch -d -n 0.5 nvidia-smi

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