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US 12,769,790 B2Granted
Neural networks to indicate data dependencies
AssigneeNVIDIA Corporation
InventorsMarc Teva Law, James Robert Lucas
Life of this patent
Estimating the term…
Abstract
Apparatuses, systems, and techniques to indicate data dependencies. In at least one embodiment, one or more neural networks are used to generate one or more indicators of one or more data dependencies and one or more indicators of direction of the one or more data dependencies.
Claims20
A processor, comprising:
- one or more circuits to:
- receive data input for a directed graph;
- use one or more neural networks to generate a spacetime embedding of the directed graph, based on the data input for the directed graph, the spacetime embedding representing one or more data dependencies and direction of the one or more data dependencies within the directed graph as one or more causal connections between events in a spacetime, wherein to generate the spacetime embedding the one or more neural networks are to restrict a connected pair of nodes of the directed graph to be represented as causally-connected events within a same convex normal neighborhood of the spacetime such that the spacetime embedding is restricted to events connected on a time-directed curve within a threshold distance of one another in the same convex normal neighborhood of the spacetime;
- and
- perform inferencing using one or more neural networks and based at least on the spacetime embedding.
2 more elements
A system, comprising memory to store executable instructions that, if executed by one or more processors, cause the system to:
- receive data input for a directed graph;
- use one or more neural networks to generate a spacetime embedding of the directed graph, based on the data input for the directed graph, the spacetime embedding representing one or more data dependencies and direction of the one or more data dependencies within the directed graph as one or more causal connections between events in a spacetime, wherein to generate the spacetime embedding the one or more neural networks are to restrict a connected pair of nodes of the directed graph to be represented as causally-connected events within a same convex normal neighborhood of the spacetime such that the spacetime embedding is restricted to events connected on a time-directed curve within a threshold distance of one another in the same convex normal neighborhood of the spacetime;
- and
- perform inferencing using one or more neural networks and based at least on the spacetime embedding.
1 more element
A method, comprising:
- receiving data input for a directed graph;
- using one or more neural networks to generate a spacetime embedding of the directed graph, based on the data input for the directed graph, the spacetime embedding representing one or more data dependencies and direction of the one or more data dependencies within the directed graph as one or more causal connections between events in a spacetime, wherein to generate the spacetime embedding the one or more neural networks are to restrict a connected pair of nodes of the directed graph to be represented as causally-connected events within a same convex normal neighborhood of the spacetime such that the spacetime embedding is restricted to events connected on a time-directed curve within a threshold distance of one another in the same convex normal neighborhood of the spacetime;
- and
- performing inferencing using one or more neural networks and based at least on the spacetime embedding.
1 more element
Dependencies are inferred from the claim text.