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Saved on Jul 23, 2020

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changes.mady.by.user Unknown User (bearceben)

Saved on Jul 23, 2020

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Planned for next month
1) Run test phase and switch competition over to docker submission. 2) Make edits to PR website videos as needed. 3) Help Carolyn with code submission and potentially docker submissions explainationsexplanations. 4) Learn about integrating Kubernetes with CodaLab for larger scale challenges. Medici will be referenced as the organizing and developing agency. 5) Integrated Okta into CodaLab for restriction to MGB users.

Planned for next month

1) Run test phase and switch competition over to docker submission.

2) Make edits to PR website videos as needed.

3) Help Carolyn with code submission and potentially docker submissions explainationsexplanations.

4) Learn about integrating Kubernetes with CodaLab for larger scale challenges. Medici will be referenced as the organizing and developing agency.

5) Integrated Okta into CodaLab for restriction to MGB users.

Comments
Things that went well: Moving data to GPU VM took a day but it's all there and seems to work. I had to create an Azure disk and mount to the VM for this. A full working example of docker submission between VMs is located here: http://miccai-staging-environment.centralus.cloudapp.azure.com/ Official secure participant docker is read on dockerhub for Organization "cpmcomps" and repo: "cpmcomps/miccai-2020:training_phase_dl_submission" pyTorch is approachable and I'm getting the hang of it. Just trained my very first model. Essentially running this on the path\rad data is all we need. Met with Eric Carmichael from CKCollab (https://www.linkedin.com/in/ericatckcollab/). He is the author of CodaLab V1 and V2 and runs a 6 person company at https://ckcollab.com/. Things that could be improved: https with queues Okta integration would be nice and I'm working on that right now as well My current understanding of pyTorch Identifying proper Azure OSes that have GPU enabled software and identify which GPUs run on them.

Comments

Things that went well:

Moving data to GPU VM took a day but it's all there and seems to work. I had to create an Azure disk and mount to the VM for this.
A full working example of docker submission between VMs is located here: http://miccai-staging-environment.centralus.cloudapp.azure.com/
Official secure participant docker is read on dockerhub for Organization "cpmcomps" and repo: "cpmcomps/miccai-2020:training_phase_dl_submission"
pyTorch is approachable and I'm getting the hang of it. Just trained my very first model. Essentially running this on the path\rad data is all we need.
Met with Eric Carmichael from CKCollab (https://www.linkedin.com/in/ericatckcollab/). He is the author of CodaLab V1 and V2 and runs a 6 person company at https://ckcollab.com/.

Things that could be improved:

https with queues
Okta integration would be nice and I'm working on that right now as well
My current understanding of pyTorch
Identifying proper Azure OSes that have GPU enabled software and identify which GPUs run on them.

Meeting	Date
Bi-weekly Meeting #1	14 May 09 Jul 2020
Bi-weekly Meeting #2	28 May 23 Jul 2020

Milestones

Description	Date
Trained my first model in pyTorch	12 May 2020	Got Miccai 2020 loaded into V2 of CodaLab	21 May 23 Jul 2020

Task

Description	Resolution	Status	Creation Date	Close Date
Create Docker image	started	pending	13 May 2020	--
Getting NIH badge	started	pending	14 May 2020	--

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