公开(公告)号：US20230007920A1

公开(公告)日：2023-01-12

申请号：US17932539

申请日：2022-09-15

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06N3/08 ,  G06T17/10 ,  G06T15/80

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.

公开(公告)号：US12045924B2

公开(公告)日：2024-07-23

申请号：US17932539

申请日：2022-09-15

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06N3/08 ,  G06T15/80 ,  G06T17/10

CPC classification number: G06T15/005 ,  G06N3/08 ,  G06T15/80 ,  G06T17/10

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.

公开(公告)号：US11481950B2

公开(公告)日：2022-10-25

申请号：US17162550

申请日：2021-01-29

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06N3/08 ,  G06T17/10 ,  G06T15/80

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.

公开(公告)号：US20210174569A1

公开(公告)日：2021-06-10

申请号：US17162550

申请日：2021-01-29

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06N3/08 ,  G06T17/10 ,  G06T15/80

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.

公开(公告)号：US10909738B2

公开(公告)日：2021-02-02

申请号：US15863780

申请日：2018-01-05

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06N3/08 ,  G06T17/10 ,  G06T15/80

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.

公开(公告)号：US20190213775A1

公开(公告)日：2019-07-11

申请号：US15863780

申请日：2018-01-05

Applicant: NVIDIA Corporation

Inventor： Rouslan L. Dimitrov ,  Dale L. Kirkland ,  Emmett M. Kilgariff ,  Sachin Satish Idgunji ,  Siddharth Sharma

IPC: G06T15/00 ,  G06T15/80 ,  G06T17/10 ,  G06N3/08

Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.