There's a small percentage of subjects that need more than the 8Gb of memory
(for mris_fix_topology if my memory is correct).
You could increase the memory allocation for all subjects, or you could run
your entire dataset with 8Gb per subject, then re-run the ones that failed with
increased mem
Hi Paul,
Thanks for your speedy response! In that case, I assume 1GB/core is the memory
allocation? Is it helpful to increase that?
Best,
Mitch
From: freesurfer-boun...@nmr.mgh.harvard.edu
on behalf of Paul Wighton
Sent: Tuesday, May 3, 2022 1:34 PM
To: Frees
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Hi Mitch,
In our experience, -openmp 8 gives faster recons than -openmp 4, but the
gains after -openmp 8 diminish quickly and aren't worth it.
-Paul
On Tue, May 3, 2022 at 12:51 PM Horn, Mitchell Jacob
wrote:
> Hi Experts,
>
>
>
> If I have 100s of
Hi Experts,
If I have 100s of subjects to recon and have access to an HPC with both GPU and
CPU options what is the recommended flags to maximize speed performance? Is …
-parallel -openmp 4 … still the best approach? And if so, is 2GB memory/core
best (keeping it 8GB memory/subject) or is there
Dear Asa,
Thank you very much for the interest in our thalamic atlas.
The atlas is defined as a tetrahedral mesh (not voxels) in its own average
space. So there is no probabilistic map in MNI space. You could try segmenting
your MNI template with FreeSurfer + the thalamic module and use that. B
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Hello Everyone,
I am trying to run mri_surf2surf. But I got some errors saying "no such file or
directory" while in fact there are files in the pathway. I was able to run this
previously, so I am not sure if this is relevant to the recent upgrade of
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Dear Experts,
I would really appreciate it if you could help me with this question:
I would like to use the probabilistic atlas of human thalamic nuclei; provided
by Iglesias et al. (2018); as a prior knowledge to locate the LGN within my
subjects (
