公开(公告)号：US20240020157A1

公开(公告)日：2024-01-18

申请号：US17862989

申请日：2022-07-12

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： MANTEJ SINGH GILL ,  DHAMODHRAN SATHYANARAYANAMURTHY ,  ARUN MAHENDRAN

IPC: G06F9/50 ,  G06N20/00

CPC classification number: G06F9/5027 ,  G06N20/00

Abstract: Systems and methods are provided for using historic input power periodic data from a server in an IT data center to train a machine learning (ML) model to obtain forecasted power consumption data of the server for a future time period. Time windows of hotspots or coldspots are then identified in the forecasted power consumption data, hotspots being defined as areas or regions of over-utilization in a time series data, and coldspots being defined as areas or regions of under-utilization in a time series data. The hotspots and coldspots are identified by calculating an exponential mean average (EMA) of the forecasted power consumption data, taking points above the EMA as hotspots and points below the EMA as coldspots. The identified hotspots and coldspots can be used to schedule workloads for a server or a data center, to more efficiently plan existing workloads, or to introduce new workloads at more optimal time periods.

公开(公告)号：US20240259034A1

公开(公告)日：2024-08-01

申请号：US18160063

申请日：2023-01-26

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： MANTEJ SINGH GILL ,  Dhamodhran SATHYANARAYANAMURTHY ,  Madhusoodhana Chari SESHA ,  Anil BABULAL

IPC: H03M7/30

CPC classification number: H03M7/6011 ,  H03M7/3073

Abstract: Systems and methods are provided for compressing a time-series dataset from a monitored device into a compressed dataset representation. Using an unsupervised machine learning model, the system may group a contiguous set of datapoints of the time-series dataset and group, using a distance algorithm, the first cluster to a first motif. A compressed dataset representation can be generated using a plurality of motifs, including the first motif, that is stored in place of the time-series dataset. This can allow the time-series dataset to be replaced with the compressed dataset representation, illustrating an overall, abstracted definition of the time-series dataset rather than the individual data points.

公开(公告)号：US20240168975A1

公开(公告)日：2024-05-23

申请号：US17991500

申请日：2022-11-21

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： MANTEJ SINGH GILL ,  MADHUSOODHANA CHARI SESHA ,  DHAMODHRAN SATHYANARAYANAMURTHY ,  ANIL BABULAL

IPC: G06F16/28 ,  G06N20/00

CPC classification number: G06F16/285 ,  G06N20/00

Abstract: Systems and methods are provided for receiving a time series dataset from a monitored processor and group the dataset into a plurality of clusters. Using an unsupervised machine learning model, the system may combine a subset of the plurality of clusters by data signature similarities to form a plurality of motifs and combine the plurality of motifs into one or more shapelets. In some examples, the system may train a supervised machine learning model using the plurality of motifs and the one or more shapelets as input to the supervised machine learning model. The system can perform various actions in response to labelling the time series dataset, including predicting a second time series dataset, determining that a monitored processor corresponds with an overutilization at a particular time, or suggesting a reduction of additional utilization of the monitored processor.