Emc Corporation

Emc IP Holding Company LLC

Dell Products Inc.

Dell & Products L.p.

Michael Robillard

Dragan Savic

Adrian Michaud

James W Espy

John Kevin Bowman

Daniel Albert Dufresne, Ii

Stephen J Todd

Victor Fong

John Victor Burroughs

Robert M Beauchamp

Himanshu Agrawal

Kenneth Durazzo

Joseph P King

Amy N Seibel

Jason Pritchard

Steven R Cieluch

Timothy Dorr

David Boudreau

Brendan Burns Healy

Daniel Savilonis

Sharon Smith

Zhen Jia

William Price Dawkins

Qiang Chen

Robert W Beauchamp

Eric Joseph Bruno

Anzhou Hou

Xuebin He

Amnon Izhar

Patrick J Weiler

Jason Stock

Gordon A Frye

Benjamin E Santaus

Bassem Bishay

Samuel Zeman

Louise Schwabe

One example method includes evaluating a function invoked by a request that is received at a local classical computing execution environment, and the request also implies performance of a quantum computing function in a quantum computing execution environment, based on an outcome of the evaluating, determining whether or not the function should be run in the local classical computing execution environment, or whether the function should be run in a separate classical computing execution environment, and when the determining indicates that the function should be run in the separate classical computing execution environment, forwarding the request to the separate classical computing environment for execution of the function. The local classical computing execution environment, the separate classical computing execution environment, and the quantum computing execution environment, are respective first, second, and third, tiers of a hybrid computing execution environment.

3-tier quantum computing execution model

One example method includes receiving, by a hybrid classical-quantum computing system, data from a node of a data confidence fabric, processing the data to create processed data, generating one or more confidence scores relating to the processed data, and making the one or more confidence scores and the processed data available to an end user. The hybrid classical-quantum computing system may also be a node of the data confidence fabric and may perform classical and/or quantum computing operations on the data.

Classical-quantum data confidence fabric

One example method includes receiving a hybrid/classical algorithm, determining a runtime characteristic of the hybrid/classical algorithm, based on the runtime characteristic, checking a memory availability for execution of the hybrid/classical algorithm, when adequate memory is not available to support execution of the hybrid/classical algorithm, modifying a classical/quantum memory fabric to provide enough memory to support execution of the hybrid/classical algorithm, and orchestrating the hybrid classical/quantum algorithm to an execution environment that includes the classical/quantum memory fabric.

Intelligent classical/quantum extended memory fabric

Techniques are disclosed for management of edge resources. For example, a method comprises receiving energy consumption data corresponding to operation of a plurality of edge devices from a plurality of edge service providers. In the method, a plurality of energy efficiency scores are computed based, at least in part, on the energy consumption data. The energy efficiency scores correspond to operation of one or more of the edge devices associated with respective ones of the edge service providers. The method further comprises receiving one or more energy consumption parameters from at least one user device for the operation of the one or more edge devices, and identifying based, at least in part, on the energy efficiency scores, a subset of the edge devices corresponding to the energy consumption parameters. Data corresponding to the subset of the edge devices is transmitted to the at least one user device.

Management of energy efficiency parameters for resources in edge computing system

Techniques are disclosed for processing unit virtualization with scalable over-provisioning in an information processing system. For example, the method accesses a data structure that maps a correspondence between a plurality of virtualized processing units and a plurality of abstracted processing units, wherein the plurality of abstracted processing units are configured to decouple an allocation decision from the plurality of virtualized processing units, and further wherein at least one of the virtualized processing units is mapped to multiple ones of the abstracted processing units. The method allocates one or more virtualized processing units to execute a given application by allocating one or more abstracted processing units identified from the data structure. The method also enables migration of one or more virtualized processing units across the system. Examples of processing units with which scalable over-provisioning functionality can be applied include, but are not limited to, accelerators such as GPUs.

Processing unit virtualization with scalable over-provisioning in an information processing system

Techniques are disclosed for management of edge devices. For example, a method comprises coordinating operation of a plurality of edge devices in a system to process a plurality of workloads. The coordinating of the operation of the plurality of edge devices in the system comprises coordinating one or more times for changing a state of at least a subset of the plurality of edge devices from a first state corresponding to a first level of activity to a second state corresponding to a second level of activity. By way of further example, the coordinating of the operation of the plurality of edge devices in the system may further comprise coordinating one or more times for the processing of the plurality of workloads by at least the subset of the plurality of edge devices in the system.

Management of performance and power consumption of edge devices

A system includes a host processor, a volatile memory device coupled to the host processor, and at least a first persistent memory device coupled to the host processor. The host processor is configured to execute one or more applications. The volatile memory device and the first persistent memory device are in respective distinct fault domains of the system, and at least one of a plurality of data objects generated by a given one of the applications is accessible from multiple distinct storage locations in respective ones of the distinct fault domains. For example, the host processor and the volatile memory device may be in a first one of the distinct fault domains and the first persistent memory device may be in a second one of the distinct fault domains. The data object remains accessible in one of the fault domains responsive to a failure in another of the fault domains.

System comprising non-volatile memory device and one or more persistent memory devices in respective fault domains

A system includes a host processor and at least one storage device coupled to the host processor. The host processor is configured to execute instructions of an instruction set, the instruction set comprising a first move instruction for moving data identified by at least one operand of the first move instruction into each of multiple distinct storage locations. The host processor, in executing the first move instruction, is configured to store the data in a first one of the storage locations identified by one or more additional operands of the first move instruction, and to store the data in a second one of the storage locations identified based at least in part on the first storage location. The instruction set in some embodiments further comprises a second move instruction for moving the data from the multiple distinct storage locations to another storage location.

Host processor configured with instruction set comprising resilient data move instructions

Systems, methods, and articles of manufacture comprising processor-readable storage media are provided for implementing server architectures having dedicated systems for processing infrastructure-related workloads. For example, a computing system includes a server node. The server node includes a first processor, a second processor, and a shared memory system. The first processor is configured to execute data computing functions of an application. The second processor is configured to execute input/output (I/O) functions for the application in parallel with the data computing functions of the application executed by the first processor. The shared memory system is configured to enable exchange of messages and data between the first and second processors.

Server architecture having dedicated compute resources for processing infrastructure-related workloads

A first endpoint comprises a fabric attach point for attachment to a memory fabric, a first media controller, and a first non-volatile memory media. The memory fabric comprises a reliability zone comprising the first endpoint and at least a second endpoint. The first media controller is configured to receive, from at least one processor coupled to the first endpoint via the at least one fabric attach point, a memory fabric store command to store an object in the reliability zone. The first media controller is further configured to store the object in the first non-volatile memory media, to receive from the second endpoint a message indicating that the same object has been stored by the second endpoint, and to send to the at least one processor a single acknowledgement indicating that the at least one object has been stored in both the first and second endpoints of the reliability zone.

Memory fabric with reliability zone comprising two or more fabric attached memory endpoints

Systems and methods are provided for implementing a memory subsystem to augment physical memory of a computing system. For example, a system comprises a memory subsystem, and a computing system coupled to the memory subsystem. The computing system comprises a processor, a first memory module, and a second memory module. The first memory module comprises random access memory which is utilized by the processor to store data associated with an application executing on the computing system. The second memory module comprises control logic circuitry that is configured to control access to the memory subsystem on behalf of the processor to store and retrieve data associated with the application executing on the computing system.

Memory subsystem to augment physical memory of a computing system

Data storage systems are provided having a segregated control plane architecture, a segregated data plane architecture, or a segregated control plane and segregated data plane architecture. For example, a data storage system includes a plurality of media nodes and a plurality of data nodes coupled to the media nodes. The media nodes control and manage persistent storage elements. Each data node includes at least one hardware processor configured to execute data plane functions and control plane functions, wherein at least one of (i) the data plane functions of a given one of the data nodes are segregated and executed by different hardware processors and (ii) the control plane functions of a given one of the data nodes are segregated and executed by different hardware processors.

Data storage system having segregated control plane and/or segregated data plane architecture

A method and computer program product for determining an internal temperature of a computing device, a power consumption factor for the computing device, and an airflow factor for the computing device. An approximated ambient air temperature is generated based upon the internal temperature, power consumption factor, and the airflow factor. A workload factor is determined for the computing device and a fan speed for the computing device is controlled based at least in part upon the approximated ambient air temperature and the workload factor.

System and method for controlling fan speed

Storage systems include a plurality of enclosures interconnected to provide a network. Each enclosure includes a first power supply module, a redundant power supply module, a first electronics module, and a redundant electronics module in electrical communication with the first electronics module and providing redundant functionality of the first electronics module. Each of the modules of each enclosure is individually associated with a separate power profile dedicated to that module. The power profile of each given module includes one or more programmable power parameters that determine when to power down and power up that given module during operation of the storage system.

Growing community of inventors

Shrewsbury, MA, United States of America

Michael Robillard