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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