公开(公告)号：US11500444B2

公开(公告)日：2022-11-15

申请号：US16870514

申请日：2020-05-08

Applicant: Intel Corporation

Inventor： Leo Aqrabawi ,  Chia-hung S. Kuo ,  James G. Hermerding, II ,  Premanand Sakarda ,  Bijan Arbab ,  Kelan Silvester

IPC: G06F1/00 ,  G06F1/3234 ,  G06F12/0815 ,  G06N5/04 ,  G06N20/00 ,  G06F1/3203

Abstract: A machine-learning (ML) scheme running a software driver stack to learn user habits of entry into low power states, such as Modern Connect Standby (ModCS), and duration depending on time of day, and/or system telemetry. The ML creates a High Water Mark (HWM) number of dirty cache lines (DL) as a hint to a power agent. A power agent algorithm uses these hints and actual system's number of DL to inform the low power state entry decision (such as S0i4 vs. S0i3 entry decision) for a computing system.

公开(公告)号：US20210349519A1

公开(公告)日：2021-11-11

申请号：US16870514

申请日：2020-05-08

Applicant: Intel Corporation

Inventor： Leo Aqrabawi ,  Chia-hung S. Kuo ,  James G. Hermerding II ,  Premanand Sakarda ,  Bijan Arbab ,  Kelan Silvester

IPC: G06F1/3234 ,  G06F12/0815 ,  G06N20/00 ,  G06N5/04

Abstract: A machine-learning (ML) scheme running a software driver stack to learn user habits of entry into low power states, such as Modern Connect Standby (ModCS), and duration depending on time of day, and/or system telemetry. The ML creates a High Water Mark (HWM) number of dirty cache lines (DL) as a hint to a power agent. A power agent algorithm uses these hints and actual system's number of DL to inform the low power state entry decision (such as S0i4 vs. S0i3 entry decision) for a computing system.