Re: [Freesurfer] Scalable recon workflow

2022-05-05 Thread Douglas N. Greve 
btw, it will almost certainly be more efficient to run each subject with 
1 thread and run them all at the same time rather than running a few of 
them with 4 or 8. If you can run them all with multiple threads, then 
that might be more efficient (depends on your scheduler, for slurm it 
would be).


On 5/3/2022 3:57 PM, Wighton, Paul wrote:
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 memory.


-Paul

*From:* freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Horn, Mitchell 
Jacob 

*Sent:* Tuesday, May 3, 2022 2:26 PM
*To:* Freesurfer support list 
*Subject:* Re: [Freesurfer] Scalable recon workflow
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:* Freesurfer support list 
*Subject:* Re: [Freesurfer] Scalable recon workflow

External Email - Use Caution

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 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 some better arrangement?

Best,

Mitch

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Re: [Freesurfer] Scalable recon workflow

2022-05-03 Thread Wighton, Paul 
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 memory.

-Paul

From: freesurfer-boun...@nmr.mgh.harvard.edu 
 on behalf of Horn, Mitchell Jacob 

Sent: Tuesday, May 3, 2022 2:26 PM
To: Freesurfer support list 
Subject: Re: [Freesurfer] Scalable recon workflow

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: Freesurfer support list 
Subject: Re: [Freesurfer] Scalable recon workflow


External Email - Use Caution

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 
mailto:mjh...@mgh.harvard.edu>> wrote:

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 some better arrangement?



Best,

Mitch









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Re: [Freesurfer] Scalable recon workflow

2022-05-03 Thread Horn, Mitchell Jacob 
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: Freesurfer support list 
Subject: Re: [Freesurfer] Scalable recon workflow


External Email - Use Caution

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 
mailto:mjh...@mgh.harvard.edu>> wrote:
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 some better arrangement?

Best,
Mitch




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Re: [Freesurfer] Scalable recon workflow

2022-05-03 Thread Paul Wighton 
External Email - Use Caution

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 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
> some better arrangement?
>
>
>
> Best,
>
> Mitch
>
>
>
>
>
>
>
>
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[Freesurfer] Scalable recon workflow

2022-05-03 Thread Horn, Mitchell Jacob 
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 some better arrangement?

Best,
Mitch




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 .
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