Systems and Methods for Segregating Machine Learned Models for Distributed Processing

A computing system of an autonomous vehicle, comprising:

• a plurality of computation resources comprising a respective plurality of processing capabilities;
• one or more tangible, non-transitory computer readable media storing computer-readable instructions that when executed by at least one of the plurality of computation resources cause the at least one of the plurality of computation resources to perform operations, the operations comprising:
• obtaining an optimized machine-learned graph model comprising a plurality of portions and portion assignment data descriptive of an assignment of each of the plurality of portions to a respective computation resource of the plurality of computation resources, wherein the plurality of portions are associated with a respective plurality of minimum processing capabilities, wherein the portion assignment data is based at least in part on the plurality of processing capabilities and the plurality of minimum processing capabilities;
• obtaining input data from one or more systems of the autonomous vehicle, wherein the input data is associated with an autonomous vehicle processing task;
• processing the input data with the optimized machine-learned graph model based at least in part on the portion assignment data to obtain output data associated with the autonomous vehicle processing task;
• and
• providing the output data to one or more additional systems of the autonomous vehicle.

One or more tangible, non-transitory computer readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations, the operations comprising:

• obtaining a graph model comprising a plurality of connected nodes;
• determining a plurality of processing capabilities for a respective plurality of computation resources;
• determining a plurality of portions from the graph model, wherein each of the plurality of portions comprises a respective subset of the plurality of nodes and a minimum processing capability;
• assigning each of the plurality of portions to a respective computation resource of the plurality of computation resources based at least in part on the minimum processing capability of a respective portion and the processing capability of the respective computation resource;
• and
• providing each of the plurality of portions to a respective computation resource to which the portion is assigned, wherein the respective computation resource is configured to process the respective portion.