MODEL LEVEL POWER CONSUMPTION OPTIMIZATION IN HARDWARE DESCRIPTION GENERATION

Patent №

US 9,355,000

Granted

2016-05-31

Filed 2011

Owner

THE MATHWORKS, INC.

Lab

AI components

1

hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

13216024

A system and method evaluates power information for a high-level model to be implemented in target hardware, and performs one or more power-reducing transmutations on the model. Transmutations may include moving one or more components from a fast rate region to a slow rate region, reducing bit width of data, signals, or other values, and replacing multiple instances of a resource with a shared instance of the resource. An in-memory representation of the model may be generated that reduces the model to a plurality of core components. A power score evaluation engine may assign power scores to the core components. Power scores may be retrieved from one or more power score database. The power scores may be non-dimensional scores representing power consumption relationships among the core components, and be target independent. Hints or alerts regarding suggested changes to the model to optimize power consumption may be presented to a user. A revised model incorporating the suggested changes may be constructed. The one or more transmutations resulting in a lowest total power score may be selected for hardware generation.

AI hardwareG06F 11/3062G06F 30/30G06F 2119/06

AI classification

AI hardware0.99
Knowledge representation0.42
Machine learning0.39
Evolutionary computation0.05
Natural language0.01
Planning0.00
Vision0.00
Speech0.00

Ownership

THE MATHWORKS, INC.

assignment · 267940018

Assignors

BISWAS, PARTHA, ZHAO, JOHN, CHEN, WANG, GU, YONGFENG

On an employer assignment, the assignors are typically the inventors.

From the same owner

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