Intel Corporation

Brinda Ganesh

Francesc Guim Bernat

Ned M Smith

Robert Valentine

Karthik Kumar

Suraj Prabhakaran

Kshitij Arun Doshi

Eric J DeHaemer

Nilesh K Jain

James R Vash

Adrian C Moga

Edwin Verplanke

Jill MacDonald Boyce

Mark Jay Charney

Zeev Sperber

Rajesh Poornachandran

Christopher J Hughes

Andrew J Herdrich

Evan Custodio

Leena K Puthiyedath

Thomas Willhalm

Eric R Delano

Rajesh M Sankaran

Amit Gradstein

Ren Wang

Alexander F Heinecke

Simon Rubanovich

Timothy Verrall

Herbert H Hum

Patrick G Kutch

Ramanathan Sethuraman

Mark A Schmisseur

Yen-Cheng Liu

Jr-Shian Tsai

James M Holland

Menachem Adelman

Dan Baum

Sameh Gobriel

Narayan Ranganathan

Swadesh Choudhary

Sumit Mohan

Yipeng Wang

Rinat Rappoport

Zhijun Lei

Somnath Paul

Evangelos Georganas

Barukh Ziv

Alexander Vul

Rashmin N Patel

Monica Kenguva

Richard Lawrence Carlson

Ganesh Kumar

David Bubien

Petar Torre

Patrick Bohan

Eric R DeLano

Trevor Cooper

Faouzi Kossentini

Tejpal Singh

Arik Narkis

Felipe Pastor Beneyto

Scott J Erlanger

Michelle M Sebot

Benjamin Graniello

Eoin Walsh

Mrittika Ganguli

Sebastian Possos

Ravi Iyer

Priya Autee

Abhirupa Layek

Sriram Kabisthalam Muthukumar

Ignacio Astilleros Diez

Regev Shemy

Abhijit Davare

Guy Boudoukh

Chekib Nouira

Foued Ben Amara

Anton Alexandrovich Sorokin

Desmond A Kirkpatrick

Suvadeep Banerjee

Monam Agarwal

Pradeep Prabhakaran

Yash Akhauri

Shaman Narayana

Craig Hurst

Hassene Tmar

Jaykant B Timbadiya

Nalini Murari

Kevin Bohan

Yaroslav Pollak

Examples include techniques for artificial intelligence (AI) capabilities at a network switch. These examples include receiving a request to register a neural network for loading to an inference resource located at the network switch and loading the neural network based on information included in the request to support an AI service to be provided by users requesting the AI service.

Techniques for artificial intelligence capabilities at a network device

Examples described herein relate to offload circuitry comprising one or more compute engines that are configurable to perform a workload offloaded from a process executed by a processor based on a descriptor particular to the workload. In some examples, the offload circuitry is configurable to perform the workload, among multiple different workloads. In some examples, the multiple different workloads include one or more of: data transformation (DT) for data format conversion, Locality Sensitive Hashing (LSH) for neural network (NN), similarity search, sparse general matrix-matrix multiplication (SpGEMM) acceleration of hash based sparse matrix multiplication, data encode, data decode, or embedding lookup.

Hardware offload circuitry

An architecture to perform resource management among multiple network nodes and associated resources is disclosed. Example resource management techniques include those relating to: proactive reservation of edge computing resources; deadline-driven resource allocation; speculative edge QoS pre-allocation; and automatic QoS migration across edge computing nodes. In a specific example, a technique for service migration includes: identifying a service operated with computing resources in an edge computing system, involving computing capabilities for a connected edge device with an identified service level; identifying a mobility condition for the service, based on a change in network connectivity with the connected edge device; and performing a migration of the service to another edge computing system based on the identified mobility condition, to enable the service to be continued at the second edge computing apparatus to provide computing capabilities for the connected edge device with the identified service level.

Quality of service (QoS) management in edge computing environments

Technologies for fulfilling service requests in an edge architecture include an edge gateway device to receive a request from an edge device or an intermediate tier device of an edge network to perform a function of a service by an entity hosting the service. The edge gateway device is to identify one or more input data to fulfill the request by the service and request the one or more input data from an edge resource identified to provide the input data. The edge gateway device is to provide the input data to the entity associated with the request.

Technologies for multi-tier prefetching in a context-aware edge gateway

A device of a service coordinating entity includes communications circuitry to communicate with a plurality of access networks via a corresponding plurality of network function virtualization (NFV) instances, processing circuitry, and a memory device. The processing circuitry is to perform operations to monitor stored performance metrics for the plurality of NFV instances. Each of the NFV instances is instantiated by a corresponding scheduler of a plurality of schedulers on a virtualization infrastructure of the service coordinating entity. A plurality of stored threshold metrics is retrieved, indicating a desired level for each of the plurality of performance metrics. A threshold condition is detected for at least one of the performance metrics for an NF V instance of the plurality of NFV instances, based on the retrieved plurality of threshold metrics. A hardware resource used by the NFV instance to communicate with an access network is adjusted based on the detected threshold condition.

Dynamic quality of service in edge cloud architectures

Example methods, apparatus, and systems to manage quality of service with respect to service level agreements in a computing device are disclosed. An example apparatus includes a first mesh proxy assigned to a first platform-agnostic application, the first mesh proxy to generate a first resource request signal based on a first service level agreement requirement from the first platform-agnostic application; a second mesh proxy assigned to a second platform-agnostic application, the second mesh proxy to generate a second resource request signal based on a second service level agreement requirement from second platform-agnostic application; and a load balancer to allocate hardware resources for the first platform-agnostic application and the second platform-agnostic application based on the first resource request signal and the second resource request signal.

Methods and apparatus to manage quality of service with respect to service level agreements in a computing device

Techniques related to distributing the video encoding processing of an input video across hardware and software systems. Such techniques include evaluating the content of the video and determine whether or the encoding operation is best to be done on the hardware system only, software system only or a hybrid hardware and software system.

Offloading video coding processes to hardware for better density-quality tradeoffs

Methods, apparatus, systems and articles of manufacture for re-use of a container in an edge computing environment are disclosed. An example method includes detecting that a container executed at an edge node of a cloud computing environment is to be cleaned, deleting user data from the container, the deletion of the user data performed without deleting the container from the memory of the edge node, restoring settings of the container to a default state; and storing information identifying the container, the information including a flavor of the container, the storing of the information to enable the container to be re-used by a subsequent requestor.

Methods and apparatus for re-use of a container in an edge computing environment

Technologies for securely providing one or more remote accelerators hosted on edge resources to a client compute device includes a device that further includes an accelerator and one or more processors. The one or more processors are to determine whether to enable acceleration of an encrypted workload, receive, via an edge network, encrypted data from a client compute device, and transfer the encrypted data to the accelerator without exposing content of the encrypted data to the one or more processors. The accelerator is to receive, in response to a determination to enable the acceleration of the encrypted workload, an accelerator key from a secure server via a secured channel, and process, in response to a transfer of the encrypted data from the one or more processors, the encrypted data using the accelerator key.

Technologies for securely providing remote accelerators hosted on the edge to client compute devices

Techniques for artificial intelligence capabilities at a network switch

Data management for edge architected computing systems extends current storage and memory schemes of edge resources to expose interfaces to allow a device, such as an endpoint or client device, or another edge resource, to specify criteria for managing data originating from the device and stored in an edge resource, and extends the storage and memory controllers to manage data in accordance with the criteria, including removing stored data that no longer satisfies the criteria. The criteria includes a temporal hint to specify a time after which the data can be removed, a physical hint to specify a list of edge resources outside of which the data can be removed, an event-based hint to specify an event after which the data can be removed, and a quality of service condition to modify the time specified in the temporal hint based on a condition, such as memory and storage capacity of the edge resource in which the data is managed.

Data management for edge architectures

Technologies for providing multi-tenant support in edge resources using edge channels include a device that includes circuitry to obtain a message associated with a service provided at the edge of a network. Additionally, the circuitry is to identify an edge channel based on metadata associated with the message. The edge channel has a predefined amount of resource capacity allocated to the edge channel to process the message. Further, the circuitry is to determine the predefined amount of resource capacity allocated to the edge channel and process the message using the allocated resource capacity for the identified edge channel.

Technologies for providing multi-tenant support using one or more edge channels

In one embodiment, a system on chip includes: a plurality of intellectual property (IP) agents formed on a semiconductor die; a mesh interconnect formed on the semiconductor die to couple the plurality of IP agents, and a plurality of mesh stops each to couple one or more of the plurality of IP agents to the mesh interconnect. The mesh interconnect may be formed of a plurality of rows each having one of a plurality of horizontal interconnects and a plurality of columns each having one of a plurality of vertical interconnects;, where at least one of the plurality of rows includes an asymmetrical number of mesh stops. Other embodiments are described and claimed.

System, apparatus and method for increasing bandwidth of edge-located agents of an integrated circuit

Growing community of inventors

Portland, OR, United States of America

Brinda Ganesh