Hewlett Packard Enterprise Development LP

Isothermal Systems Research, Inc.

Nvidia Corporation

Dcg Systems Gmbh

Hewlett-Packard Development Company, L.p.

Credence Systems Corporation

Mellanox Technologies, Ltd.

Tahir Cader

John P Franz

Harvey John Lunsman

David Allen Moore

Charles Lester Tilton

Matthew Richard Slaby

Michael Lawrence Sabotta

George Joseph Wos

Ernesto Ferrer Medina

Wade David Vinson

Cullen Edwin Bash

Jonathan Frank

Thomas Wong

Elad Mentovich

Greg Scott Long

Donald E Tilton

Sergey Serebryakov

Ernesto Ferrer

Mehmet Kivanc Ozonat

Ryan Kelsey Albright

Benjamin Goska

Michael Thompson

Aaron Richard Carkin

William Ryan Weese

Ratnesh Kumar Sharma

Zhiyong Li

Siamak Tavallaei

William Andrew Mecham

Martin Arlitt

Minh H Nguyen

Anita Rogacs

Hai Ngoc Nguyen

Steven J Dean

Paul Allan Knight

Chris Deon Hyser

Zhikui Wang

Steven Kasapi

David Paul Mohr

Nader Pakdaman

Alan B Doerr

Scott P Faasse

Michael Scott

Javier F Izquierdo

Siddha Ganju

Jon Kolas

Susheela N Narasimhan

Thomas Robert Bowden

Nathan G Muoio

Benjamin Hewett Tolman

William Kirk Norton

Alan Brent Roberts

Tuong Q Tran

Douglas Kent Garday

Niru Kumari

Ryan J Baddeley

Sergio Escobar-Vargas

Aaron Childers

Jeff Hanson

Sammy L Zimmerman, Sr

Robert J Ressa

Felipe Visbal

Rongliang Zhou

Jeffrey A Plank

Marc E Davis

Jordan Levy

Richard A Bargerhuff

Ran Hasson Ruso

Keith Mathew McAuliffe

Mark Joseph Lepore

Nanjundaiah Deepak

Richard Shaw Kaufmann

Boaz Atias

Gardson Githu

Steve Roscio

Mitchell Johnson

Fred Devoir

Nathan Stoddard

Elijah Chen

Sarah Anthony

Zhiki Wang

Cullen E Base

Deepak Nanjundaiah

Chunjian Ni

Donald D Tilton

Ameya Soparkar

Aaron Michael Childers

Sammy L Zimmerman Sr

David Moore

Systems and methods are provided for improving statistical and machine learning drift detection models that monitor computing health of a data center environment. For example, the system can receive streams of sensor data from a plurality of sensors in a data center; clean the streams of sensor data; generate, using a machine learning (ML) model, an anomaly score and a dynamic threshold value based on the cleaned streams of sensor data; determine, using the ML model and based on the anomaly score and the dynamic threshold value, a correctness indicator for a first sensor in the plurality of sensors; and using the correctness indicator, correct the first sensor.

Improving data monitoring and quality using AI and machine learning

A method includes determining, using a processing device, a set of observations from coolant data, the coolant data being received from one or more sensors in an environment associated with a coolant. The method further includes determining, using a machine learning model and the set of observations, a contamination level of the coolant. The method also includes initiating an operation, using the processing device, responsive to determining the coolant contamination level.

Fluid inspection using machine learning

An example device includes processing circuitry and a memory. The memory includes instructions that cause the device to perform various functions. The functions include receiving datastreams from a plurality of sensors of a high performance computing system, classifying each datastream of the each sensor to one of a plurality of datastream models, selecting an anomaly detection algorithm from a plurality of anomaly detection algorithms for each datastream, determining parameters of the each anomaly detection algorithm, determining an anomaly threshold for each datastream, and generating an indication that the sensor associated with the datastream is acting anomalously.

Classification based anomaly detection

Example implementations relate to a chassis cooling resource. In some examples, a chassis cooling resource includes a controller, comprising instructions to detect a failure corresponding to a first cooling system of a first chassis coupled to a server rack, and alter settings of a second cooling system of a second chassis coupled the server rack to provide additional cooling resources to the first cooling system in response to the detected failure.

Chassis cooling resource

A circuit board cooling apparatus is disclosed having a heat spreader device to be thermally coupled with a surface of the circuit board to be cooled. Also, a conforming heat transfer device is disclosed that is thermally and physically coupled with the heat spreader device to conform to a surface contour of the heat spreader device on a first side of the heat transfer device. The cooling apparatus also includes a heat transport device physically attached and thermally coupled with a second side of the heat transfer device.

Conforming heat transport device for dual inline memory module cooling applications

One aspect described in this application provides an apparatus that includes an external tray hose with an integrated booster pump for cooling a computing device. The booster pump can boost fluid flow and fluid pressure of coolant fluid pumped toward the computing device on a server tray. The booster pump includes a stator mounted around a booster pump housing with a bore. The stator includes one or more C-shaped lamination stacks for supporting coil windings. Energized coil windings generate a varying magnetic field for rotating an impeller within a housing bore to pump fluid along the housing bore of the booster pump. The apparatus includes a monitor module to monitor a set of sensors to obtain information about one or more of fluid temperature, fluid pressure, and device temperature; and a control module to adjust performance of the booster pump based on the information obtained from the set of sensors.

External tray hose with integrated pump

Example implementations relate to a cooling module, and a method of cooling an electronic circuit module. The cooling module includes first and second cooling components fluidically connected to each other. The first cooling component includes a first fluid channel having supply, return, and body sections, and a second fluid channel. The second cooling component includes an intermediate fluid channel. The body section is bifurcated into first and second body sections, and the first and second body sections are further merged into a third body section. The supply section is connected to the first and second body sections. The return section is connected to the third body section and the intermediate fluid channel via an inlet fluid-flow path established between the first and second cooling components. The second fluid channel is connected to the intermediate fluid channel via an outlet fluid-flow path established between the first and second cooling components.

Variable flow liquid-cooled cooling module

Devices, apparatuses, systems, and methods are provided for improved thermal management in networking computing devices. An example thermal management apparatus includes a housing defining a first end and a second end opposite the first end. The apparatus further includes an electronic component supported within the housing, such as a GPU. The apparatus includes a primary inlet that receives a primary airflow having a first temperature and a secondary inlet that receives a secondary airflow having a second temperature where the second temperature is different than the first temperature. The primary airflow and the secondary airflow are collectively configured to dissipate heat generated by the electronic component.

Computing devices with improved thermal management

Systems and methods are provided for utilizing a bidirectional intermediate data transport layer to connect multiple customers to a shared, cloud-based AIOps service. As a feature of the intermediate data transport layer, each customer (and their data) may be isolated from other customers. In various examples, the cloud-based AIOps service may receive sensor data from customer systems via the intermediate data transport layer. The cloud-based AIOps service may analyze this sensor data (e.g. detect anomalies, perform root cause analyses, find optimal conditions, etc.), and modify the operation of one or more of the customer systems (e.g. modify the settings/configuration of a sensor on a piece of connected infrastructure) via the intermediate data transport layer. In certain examples, in addition to (or instead of) modifying the operation of one or more of the customer systems, the cloud-based AIOps service may provide an on-premises notification to a customer.

AIOps as a cloud-based service

A power arrangement and cooling system for electronic devices includes a processing unit electrically interconnected and disposed to a first side of a printed circuit board and a power converter electrically interconnected and disposed on a second side of the printed circuit board. The power converter includes a thermally conductive material layer that transfers heat generated by the power converter during operation away from the power converter toward a heatsink that is disposed adjacent the second side of the printed circuit board. Heat generated by the processing unit is absorbed by a heatsink disposed adjacent the first side of the printed circuit board. Power for the processing unit is provided, by the power converter, through a thickness of the printed circuit board.

Power arrangement and cooling system for electronic devices

In the examples provided herein, a system includes an electrochemical sensor having two electrodes inserted in a fluid to be tested, where an alternative current (AC) voltage is applied across the two electrodes; an electrochemical sensor having two electrodes inserted in a fluid to be tested, wherein an alternative current (AC) voltage across the two electrodes; and a frequency response analyzer to analyze the measured the electrical response across multiple frequencies. The system also includes a memory to store a baseline of the electrical response across multiple frequencies, and a processor to determine from the stored baseline and the measured electrical response whether the electrical response is outside a predetermined range.

Electrical frequency response fluid analysis

Cooling module and a method of cooling an electronic circuit module using the cooling module

Growing community of inventors

Liberty Lake, WA, United States of America

Tahir Cader