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HumanBrainProject / hbp-spatial-backend

An HTTP backend for transforming coordinates and data between the core template spaces of the HBP
Apache License 2.0
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migration from openshift (CSCS) to kubernetes #4

Open xgui3783 opened 11 months ago

xgui3783 commented 11 months ago

Dear @ylep @JoelChavas ,

The openshift cluster at CSCS will be discontinued at the end of year. I am currently in the process of migrating all of the existing services (including hbp-spatial-backend) to a kubernetes (k8s) cluster (not openshift). (My understanding was that there were difficulties getting openshift to run on the new sites.

As I have developer access on the OKD project, I believe I should be able to handle the migration.

However, some documentation should be added (re: deployment configuration on the new cluster, updated URL etc).

I would like to use this issue to track the migration progress.

Question

In normal operation how much RAM on average/at max would the process need? (The new cluster is more constrained, and we will need to budget the resources)

Progress

ylep commented 10 months ago

In normal operation how much RAM on average/at max would the process need? (The new cluster is more constrained, and we will need to budget the resources)

The process is not so much CPU-bound, but rather memory and maybe I/O could be a bottleneck. The AimsApplyTransform process needs to load the full deformation fields from disk into RAM, which is essentially the size of the .ima files (about 1 GB for BigBrain, < 100 MB for the other templates). There may be some overheads / suboptimal memory usage e.g. data duplication, but I think 2-3 GB of available RAM should be enough.

xgui3783 commented 10 months ago

Thanks for the comment.

I am also curious, regarding the .ima files, they are currently manually curated / managed (I manually downloaded the file from the okd deployment, and uploaded to the new k8s cluster), is the file available programmatically (e.g. via http/ftp somewhere?) I can imagine we can make the deployment process a lot more automatic, and better documented.

ylep commented 10 months ago

@xgui3783 the .ima files should in theory be identical to those in the KnowledgeGraph (DOI 10.25493/GA3Y-9V8). However, I just double-checked and it appears that the curated version is not the most up-to-date:

Here is the change log that appears at the top of my latest version of the graph.yaml file:

# 2021-07-29  Yann Leprince  <yann.leprince@cea.fr>
#
#     Important fix of an error in the BigBrain transformation; support for
#     transforming images.
#
#     * *.ima.minf: fix the header transformations in the deformation fields,
#     because they will be used by AimsApplyTransform in order to transform
#     images (since the deformation fields are passed to --reference, see
#     https://github.com/HumanBrainProject/hbp-spatial-backend/blob/515ee51fb6c4f4df06bd6bc02e18e4ccfeaaf1bc/hbp_spatial_backend/api_v1.py#L321).
#     The transformations in *_AIMS_TO_template.trm have been copied into the
#     header of each corresponding deformation field.
#
#     * bigbrain_AIMS_TO_template.trm: fix incorrect value of the
#     transformation (the previous version was offset by about 5 millimetres).
#
# 2021-07-28  Yann Leprince  <yann.leprince@cea.fr>
#
#     * graph.yaml: for consistency, restore the "inv:" prefix in the
#     transformation from "MNI 152 ICBM 2009c Nonlinear Asymmetric" to its AIMS
#     referential. Note that this does not change anything to the results, as
#     this transformation is its own inverse.
#
# 2019-03-07  Yann Leprince  <yann.leprince@cea.fr>
#
#     Initial release of the cross-template transformations.

I probably should have sent the updated version for curation back in 2021... but maybe it is not too late

ylep commented 10 months ago

Here is the patch file that goes from the current KnowledgeGraph version to the latest: https://gist.github.com/ylep/3614931a52b12ced591f49a2ec7c892b

denisri commented 10 months ago

If this is an issue, it is probably also possible to switch the .ima files to nifti format, which is more standard. But we would need to make a new version of the data in the knowledge graph too.