System and method for executing self-evolving property graphs on GPU hardware
A system and method for self-executing graphs wherein execution semantics are encoded within graph elements themselves rather than imposed by external schedulers. The system comprises a dynamic property graph with vertices and edges that encode execution semantics specifying computational operations and graph-internal triggering conditions. An execution engine evaluates these triggering conditions by monitoring graph state, detects satisfaction through graph-internal evaluation, and initiates bound computational operations. Triggering conditions are expressed in terms of vertex or edge traversal, property changes, geometric properties such as curvature, or topological connectivity patterns. The graph autonomously determines when and which operations execute based on graph-resident execution semantics. In distributed embodiments, multiple local coordinators evaluate triggers within assigned graph regions and coordinate through peer-to-peer messaging without centralized scheduling. Applications include autonomous cognitive systems, adaptive control systems, and scalable distributed computation requiring self-regulating execution without centralized bottlenecks.
1 . A computer-implemented system for executing self-executing graphs, comprising:
a memory and one or more processors;
a dynamic property graph comprising vertices and edges, at least a subset of the vertices or edges encoding execution semantics that specify:
one or more computational operations to be performed on the dynamic property graph; and
one or more graph-internal triggering conditions expressed in terms of at least one of: traversal of vertices or edges, changes in vertex or edge properties, geometric properties of graph regions, or topological properties of graph structure;
an execution engine configured to:
evaluate the graph-internal triggering conditions encoded in the execution semantics by monitoring graph state;
detect satisfaction of said triggering conditions through graph-internal evaluation;
initiate the computational operations bound to satisfied triggering conditions; and
execute said computational operations to modify the dynamic property graph;
wherein the dynamic property graph determines when and which computational operations execute based on the graph-internal triggering conditions encoded in the execution semantics.
2 . The system of claim 1 , wherein the one or more processors comprise one or more graphics processing units, and wherein the computational operations comprise operator kernels executable on the graphics processing units.
3 . The system of claim 2 , wherein the operator kernels comprise geometric operators including at least one of: diffusion operators, geodesic operators, curvature operators, spectral operators, or recombination operators.
4 . The system of claim 1 , wherein the execution semantics further encode execution constraints comprising at least one of: rate limits on operation invocation frequency, resource limits on computational resource consumption, or priority specifications for operation scheduling.
5 . The system of claim 1 , wherein the execution engine comprises:
a trigger coordinator configured to evaluate the graph-internal triggering conditions; and
a regulation enforcer configured to gate initiation of the computational operations based on execution constraints encoded in the execution semantics.
6 . The system of claim 1 , wherein the vertices comprise event vertices representing experiential inputs and communication vertices representing information exchanges.
7 . The system of claim 1 , wherein the graph-internal triggering conditions comprise at least one of: traversal-based triggers that initiate computational operations based on vertex or edge visitation frequency, state-change triggers that initiate computational operations upon property modifications, geometric triggers that initiate computational operations based on curvature values or flow properties, or topological triggers that initiate computational operations based on connectivity patterns.
8 . The system of claim 1 , wherein the dynamic property graph is partitioned into a plurality of graph regions, and wherein the system further comprises a plurality of local coordinators, each local coordinator configured to evaluate graph-internal triggering conditions within an assigned graph region and to communicate with other local coordinators via peer-to-peer messaging.
9 . The system of claim 1 , wherein the execution engine is configured to evaluate the graph-internal triggering conditions continuously as the dynamic property graph evolves through execution of the computational operations.
10 . The system of claim 1 , wherein the computational operations modify the dynamic property graph by at least one of: creating vertices or edges, deleting vertices or edges, modifying properties of vertices or edges, or modifying the execution semantics encoded in vertices or edges.
11 . A computer-implemented method for executing self-executing graphs, comprising the steps of:
providing a dynamic property graph comprising vertices and edges, at least a subset of the vertices or edges encoding execution semantics that specify:
one or more computational operations to be performed on the dynamic property graph; and
one or more graph-internal triggering conditions expressed in terms of at least one of: traversal of vertices or edges, changes in vertex or edge properties, geometric properties of graph regions, or topological properties of graph structure;
evaluating, by an execution engine, the graph-internal triggering conditions encoded in the execution semantics by monitoring graph state;
detecting satisfaction of said triggering conditions through graph-internal evaluation;
initiating the computational operations bound to satisfied triggering conditions; and
executing said computational operations to modify the dynamic property graph;
wherein the dynamic property graph determines when and which computational operations execute based on the graph-internal triggering conditions encoded in the execution semantics.
12 . The method of claim 11 , wherein evaluating the graph-internal triggering conditions and executing the computational operations are performed using one or more graphics processing units, and wherein the computational operations comprise operator kernels executable on the graphics processing units.
13 . The method of claim 12 , wherein the operator kernels comprise geometric operators including at least one of: diffusion operators, geodesic operators, curvature operators, spectral operators, or recombination operators.
14 . The method of claim 11 , wherein the execution semantics further encode execution constraints comprising at least one of: rate limits on operation invocation frequency, resource limits on computational resource consumption, or priority specifications for operation scheduling, and wherein the method further comprises enforcing said execution constraints prior to initiating the computational operations.
15 . The method of claim 11 , further comprising:
evaluating, by a trigger coordinator, the graph-internal triggering conditions; and
gating, by a regulation enforcer, initiation of the computational operations based on execution constraints encoded in the execution semantics.
16 . The method of claim 11 , wherein the vertices comprise event vertices representing experiential inputs and communication vertices representing information exchanges.
17 . The method of claim 11 , wherein the graph-internal triggering conditions comprise at least one of: traversal-based triggers that initiate computational operations based on vertex or edge visitation frequency, state-change triggers that initiate computational operations upon property modifications, geometric triggers that initiate computational operations based on curvature values or flow properties, or topological triggers that initiate computational operations based on connectivity patterns.
18 . The method of claim 11 , wherein the dynamic property graph is partitioned into a plurality of graph regions, and wherein the method further comprises:
evaluating, by a plurality of local coordinators, graph-internal triggering conditions within respective assigned graph regions; and
communicating between the local coordinators via peer-to-peer messaging to coordinate execution affecting multiple graph regions.
19 . The method of claim 11 , wherein evaluating the graph-internal triggering conditions occurs continuously as the dynamic property graph evolves through execution of the computational operations.
20 . The method of claim 11 , wherein executing the computational operations comprises modifying the dynamic property graph by at least one of: creating vertices or edges, deleting vertices or edges, modifying properties of vertices or edges, or modifying the execution semantics encoded in vertices or edges.