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At Sage, we generally provision an EC2 Linux instance for a Challenge that leverages SynapseWorkflowOrchestrator to run CWL workflows. These workflows will be responsible for evaluating and scoring submissions (see model-to-data-challenge-workflow GitHub for an example workflow). If Sage is responsible for the cloud compute services, please give a general estimate of the computing power (memory, volume) needed. We can also help with the estimates if you are unsure.
What Can Affect the Computing Power
By default, up to ten submissions can be evaluated concurrently, though this number can be increased or decreased accordingly within the orchestrator's .env file. Generally, the more submissions you want to run concurrently, the more power will be required of the instance.
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The volume of the instance will be dependent on variables such as the size of the input files and the generated output files. If running a model-to-data challenge, Docker images should also be taken into account. On average, participants will create Docker images that are around 2-4 GB in size, though some have reached up to >10 GB. (When this happens, we do encourage participants to revisit their Dockerfile and source code to ensure they are following best practices, as >10 GB is a bit high).
Sensitive Data
If data is sensitive and cannot leave the external site or data provider, please provide a remote server with (ideally) the following:
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Important!! After the initial copying, all changes to the live site should now be synced over with mirror-wiki; DO NOT use copyWiki again. More on updating the Wikis under Update the Challenge.
Stop the Orchestrator
15. On the instance, enter:
Ctrl + C
followed by:
docker-compose down
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