Bugfix: cross-validation with few memory

[csapot]

the "cross-validate" run of train_tool did not use the $cache_size parameter, so it went to a memory allocation error
(using 8 GB RAM)

[bpotard]

Well spotted! However I think if you run out of memory in the cross validation, it must be because you are using a GPU with a very limited amount of memory. It is the on-board GPU memory which is the limiting factor in CUDA mode, note your "main" RAM. With that recipe, the cross-validation should really take no more than a few hundred MB. If you do not have a decent GPU, you may be better off using the CPU rather than the GPU.

[csapot]

You are right, I only have a 1 GB GPU currently.
I also tried running on CPU on a different computer, and it was working
fine without memory errors (but much slower).

On 2016.07.20. 11:11, Blaise Potard wrote:

Well spotted! However I think if you run out of memory in the cross
validation, it must be because you are using a GPU with a very limited
amount of memory. It is the on-board GPU memory which is the limiting
factor in CUDA mode, note your "main" RAM. With that recipe, the
cross-validation should really take no more than a few hundred MB. If
you do not have a decent GPU, you may be better off using the CPU
rather than the GPU.

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[bpotard]

Ok, you are better off using the GPU then. It should be easier now with your fix.
1GB should be plenty though, I am a bit surprised the cross-validation would take that much. Maybe you have other processes using the GPU, i.e. you can try to run nvidia-smi to see if there is another process clogging your GPU memory.

[bpotard]

Ah no, you are right, with the default settings it takes close to 3GB of GPU memory.

[csapot]

No, I don't have anything else, even the X server is disabled. After
some trials I found that a "cache-size" of 10000 works fine.

On 2016.07.20. 12:08, Blaise Potard wrote:

Ah no, you are right, with the default settings it takes close to 3GB
of GPU memory.

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