1. A method, comprising: identifying one or more structures recurring across multiple model files, wherein each model file comprises information relating to one or more neurosynaptic cores; for each recurring structure identified, generating a corresponding reusable compositional prototype, wherein each reusable compositional prototype comprises one or more metadata tags and a set of pre-defined rules, and each rule identifies one or more modifications for a neurosynaptic network; maintaining a library including each reusable compositional prototype generated; in response to receiving one or more search parameters, searching the library based on the one or more search parameters; selecting at least one reusable compositional prototype with at least one metadata tag satisfying the one or more search parameters; and instantiating one or more components of the network and connectivity between the one or more components based on one or more rules included in the at least one selected reusable compositional prototype, thereby decreasing time associated with developing and debugging the network and increasing accuracy of the network.
1. A method, comprising: identifying one or more structures recurring across multiple model files, wherein each model file comprises information relating to one or more neurosynaptic cores; for each recurring structure identified, generating a corresponding reusable compositional prototype, wherein each reusable compositional prototype comprises one or more metadata tags and a set of pre-defined rules, and each rule identifies one or more modifications for a neurosynaptic network; maintaining a library including each reusable compositional prototype generated; in response to receiving one or more search parameters, searching the library based on the one or more search parameters; selecting at least one reusable compositional prototype with at least one metadata tag satisfying the one or more search parameters; and instantiating one or more components of the network and connectivity between the one or more components based on one or more rules included in the at least one selected reusable compositional prototype, thereby decreasing time associated with developing and debugging the network and increasing accuracy of the network. 7. The method of claim 1 , wherein the one or more neurosynaptic programs are instantiated in a distributed environment.