Open p-j-smith opened 1 year ago
I think a GPU is not required, but the analysis will run significantly faster on GPU
Pricing per month if we use CPU vs GPU, and have ec2 instance running continually vs using EKS to launch containers:
Prices are in $USD
This pricing assumes usage of 40 hours per week (8 hours a day times 5 days per week) when running directly on ec2, and 5 hours per week (1 hour per day time 5 days per week) when running via EKS. The cost of running EKS is $73.00 USD per month ($0.10 USD per hour).
So running the analysis on CPU only (without EKS) is the most cost effective (assuming the usage estimates are accurate). In #44 let's see how long the analysis takes to run on the CPU
After some test runs for #44, seems that a GPU is indeed required to run FastSurfer. See also https://github.com/UCL-MIRSG/xnat-aws/issues/67#issuecomment-1678778159
In https://github.com/UCL-MIRSG/xnat-aws/issues/67#issuecomment-1678778159 you said:
...now I'm getting a new one:
Could not create container from image healthbioscienceideas/fastsurfer:gpu
which command was that for? I just tried running Converts NIFTI to 256 conformed MGZ file
on the output from Run dcm2niix on a Scan
and got this error:
/fastsurfer/nii_to_mgz.sh: line 27: pydeface: command not found
Deface failed
I had it from that same command
I just ran the Defaces a T1 Nifti scan
command on the same output from Run dcm2niix on a Scan
and it ran okay - it took about 13 minutes.
Then I tried running the DEFACED DATA - Converts defaced NIFTI to 256 conformed MGZ file
on the defaced output and got the same error:
/fastsurfer/nii_to_mgz.sh: line 27: pydeface: command not found
Deface failed
We could try using the healthbioscienceideas/pydeface:latest
tag of the image rather than healthbioscienceideas/pydeface:minify
- the minify version must not have pydeface installed
Oh, so you got it to run without a GPU?
OK so I got the same error as you now. So it seems we don't need a GPU after all?
Not sure why it wasn't working before for me... I did destroy and re-deploy the architecture though, so that might have resolved the Could not create container from image healthbioscienceideas/fastsurfer:gpu
problem.
Created another issue for this #70
Since it doesn't seem essential after all, maybe we could provide it as an option? In #72 I created separate commands to run FastSurfer on a GPU or CPU, so we could let users decide which one they want to use.
The workshop uses a container that runs some analysis with Fastsurfer. This requires a GPU to run, so we should change the ec2 instance type we're using for the Container Service