公开(公告)号：US11487341B2

公开(公告)日：2022-11-01

申请号：US16460615

申请日：2019-07-02

Applicant: NVIDIA Corporation

Inventor： Aniket Naik ,  Tezaswi Raja ,  Kevin Wilder ,  Rajeshwaran Selvanesan ,  Divya Ramakrishnan ,  Daniel Rodriguez ,  Benjamin Faulkner ,  Raj Jayakar ,  Fei (Walter) Li

IPC: G06F1/324 ,  G06F9/38

Abstract: Systems and techniques for improving the performance of circuits while adapting to dynamic voltage drops caused by the execution of noisy instructions (e.g. high power consuming instructions) are provided. The performance is improved by slowing down the frequency of operation selectively for types of noisy instructions. An example technique controls a clock by detecting an instruction of a predetermined noisy type that is predicted to have a predefined noise characteristic (e.g. a high level of noise generated on the voltage rails of a circuit due to greater amount of current drawn by the instruction), and, responsive to the detecting, deceasing a frequency of the clock. The detecting occurs before execution of the instruction. The changing of the frequency in accordance with instruction type enables the circuits to be operated at high frequencies even if some of the workloads include instructions for which the frequency of operation is slowed down.

公开(公告)号：US11379708B2

公开(公告)日：2022-07-05

申请号：US16514078

申请日：2019-07-17

Applicant: NVIDIA Corporation

Inventor： Sachin Idgunji ,  Ming Y. Siu ,  Alex Gu ,  James Reilley ,  Manan Patel ,  Rajeshwaran Selvanesan ,  Ewa Kubalska

IPC: G06F9/30 ,  G06N3/04 ,  G06N3/08 ,  G06F9/38 ,  G06F1/3206

Abstract: An integrated circuit such as, for example a graphics processing unit (GPU), includes a dynamic power controller for adjusting operating voltage and/or frequency. The controller may receive current power used by the integrated circuit and a predicted power determined based on instructions pending in a plurality of processors. The controller determines adjustments that need to be made to the operating voltage and/or frequency to minimize the difference between the current power and the predicted power. An in-system reinforced learning mechanism is included to self-tune parameters of the controller.