3. The computer-implemented method of claim 1 , further comprising: assigning a system resource quota to at least one respective user; determining an amount of system resources that the model implementations for the respective user have consumed over a given period of time; and selecting the model implementation based on an amount of unconsumed system resources according to the system resource quota, wherein an amount of system resources that can be consumed by the selected model implementation does not exceed the amount of unconsumed system resources.
1. A computer-implemented method, the method comprising: for each representation of a plurality of representations of predictive models, selecting a model implementation from a plurality of model implementation for the representation, wherein each representation is associated with a respective user and comprises a description of a respective predictive model, the selection based on a status of the representation's respective user; associating each of the model implementations with a respective node in a directed graph wherein for one or more ordered pairs of nodes in the graph the prediction output of a model implementation associated with a first node in the pair serves as input to a model implementation associated with a second node in the pair; determining, from the directed graph, a subset of model implementations that can be executed in parallel based on edge dependencies in the directed graph; and causing the models in the subset of model implementations to be executed in parallel.