Invention Grant
- Patent Title: Allocating resources for a machine learning model
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Application No.: US16827376Application Date: 2020-03-23
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Publication No.: US11138522B1Publication Date: 2021-10-05
- Inventor: Jonathan Ross , John Michael Stivoric
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F9/50 ; G06F9/48 ; G06F8/41

Abstract:
A method for allocating resources for a machine learning model is disclosed. A machine learning model to be executed on a special purpose machine learning model processor is received. A computational data graph is generated from the machine learning model. The computational dataflow graph represents the machine learning model which includes nodes, connector directed edges, and parameter directed edges. The operations of the computational dataflow graph is scheduled and then compiled using a deterministic instruction set architecture that specifies functionality of a special purpose machine learning model processor. An amount of resources required to execute the computational dataflow graph is determined. Resources are allocated based on the determined amounts of resources required to execute the machine learning model represented by the computational dataflow graph.
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