Try out an algorithm
Prior to using an algorithm, you need to request access. You do not need to request permission if you are using your own algorithm. To request access, navigate to the algorithm, and click on "Request Access", as shown below. This request needs to be accepted by the Algorithm Editors before you can use the algorithm. If the Algorithm Editors do not respond, the Grand Challenge support cannot bypass this verification step. If this happens, you can contact the Algorithm Editors directly through their contact email listed on the algorithm page.
The easiest way to start a job is by navigating clicking on the Try-out Algorithm option from the side menu or from the Results page
On this page, you can simply drag and drop your inputs or images, and then click on the Save button to start the job.
Connect an Algorithm to an Archive
Another way to run an algorithm job is to connect an Algorithm to an Archive. Go to your Archive → Update Settings → select an Algorithm.
The third way to run algorithm jobs is to use the Grand Challenge API Client to start an algorithm job through Python.
Each method will require you to provide all the inputs defined for the algorithm. After submitting the inputs, the algorithm job will be queued and the job will be visible on the Results page.
To try out your own algorithm, you will have to wait until your algorithm container is uploaded and . You can check the status of your container by clicking on Containers. Normally, it takes about 20 minutes for your new container to be validated by grand-challenge.org and to become active.
To view the results of your jobs, click on the Results page and then click on your result to view the outputs, or click Open Result in Viewer to view your image with one of our image viewers.
When you click you Open Result in Viewer, you will be redirected to a CIRRUS viewer that will display the outputs of the algorithm like in this example from the CORADS-AI algorithm.
💳 An algorithm editor can choose to ask for credits from users who want to try out the algorithm. These can be set by the editor in the algorithm settings. A credit of 0 means users can run the algorithm an unlimited number of times. If a credit value above 0 is set, these will be deducted from the users' credits whenever they submit a file to run the algorithm on. A user has 1000 credits per month at their disposal.
Job execution times
⚠️ The algorithm jobs are executed on AWS ECS and rely on spot instances. This means that the job will only be executed when a spot instance becomes available, a job will remain in the Executing status while waiting for a spot instance. There is no way to predict how long it will take before a spot becomes available (might take more than a day) or to move a job further up in the queue.
Job status meaning
When you start an algorithm job it progresses through a number of different states. First, the job is provisioned (i.e., prepared for execution), then the job is sent to AWS, where it get assigned to an EC2 spot instance for execution. This step can take a while and there is no way to predict how long it takes. While this happens your job will be in "executing" status. The "executing" status thus does not necessarily mean that your algorithm is being executed, but rather that it is being processed on Amazon ECS, where it can be in any of the states described here. This means that your algorithm can be in "executing" state for a long time, irrespective of how long your algorithm takes to run on your local machine. Once the algorithm job has run, your job's status will update to either "failed" or "successful". If your status is "cancelled" the job was manually cancelled by one of our admins.