Conditional graph execution based on prior simplified graph execution
AssigneeTenstorrent Inc.
InventorsLjubisa Bajic, Milos Trajkovic, Ivan Hamer
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Abstract
Computer-implemented methods and associated hardware for executing directed graphs are disclosed herein. An example method includes deriving a simplified version of a directed graph, applying a pilot input tensor to the simplified version of the directed graph, and obtaining a collection of execution data during the application of the pilot input tensor to the simplified version of the directed graph. The method also includes applying a live input tensor to the directed graph and conditioning the execution of the directed graph using the collection of execution data. An output tensor is obtained from the conditional execution of the directed graph.
Claims30
A computer-implemented method for executing a directed graph, in which each step is conducted by a processor, comprising:
- deriving a simplified version of the directed graph;
- applying a pilot input tensor to the simplified version of the directed graph;
- obtaining a collection of execution data during the application of the pilot input tensor to the simplified version of the directed graph;
- applying a live input tensor to the directed graph;
- conditioning the execution of the directed graph, during the application of the live input tensor to the directed graph, using the collection of execution data;
- and
- obtaining an output tensor from the conditional execution of the directed graph.
A system for executing a directed graph comprising:
- a means for deriving a simplified version of the directed graph;
- a means for applying a pilot input tensor to the simplified version of the directed graph;
- a means for obtaining a collection of execution data during the application of the pilot input tensor to the simplified version of the directed graph;
- a means for applying a live input tensor to the directed graph;
- a means for conditioning the execution of the directed graph, during the application of the live input tensor to the directed graph, using the collection of execution data;
- and
- a means for obtaining an output tensor from the conditional execution of the directed graph.
A computer-implemented method for generating an inference from a neural network, in which each step is conducted by a processor, comprising:
- deriving a simplified version of the neural network;
- applying a first input to the simplified version of the neural network;
- obtaining a collection of execution data during the application of the first input to the neural network;
- applying a second input to the neural network;
- conditioning the computation of the neural network, during the application of the second input to the neural network;
- and
- obtaining an inference from the conditional computation of the neural network;
- wherein the conditional computation of the neural network is conditioned using the execution data;
- and
- the conditional computation of the neural network is less computationally intensive than a non-conditional computation of the neural network using the second input.
Dependencies are inferred from the claim text.