15 results about "Scalable architecture" patented technology

Enhanced Common Packet Radio Interface (eCPRI) based Fronthaul forms the foundation for open radio access network (O-RAN). O-RAN envisages splitting the radio into two parts, a Distributed Unit (DU) and Radio Units (RU), interconnected using high speed Fronthaul links. O-RAN and eCPRI for 5G / NR place demands for high speed Fronthaul with low latency, and high network bandwidth requirements. In the present disclosure, embodiments for configurable eCPRI Fronthaul solutions are disclosed. Various hardware accelerator implementations are presented for control plane and user plane traffic. The hardware accelerator implementation may support DU and RRU functionality required by eCPRI with minimal software intervention. The configurable eCPRI Fronthaul may support different data flows and meet different performance demands of DU and RRU. Scalable architecture may be applied for the configurable eCPRI Fronthaul to allow stacking of multiple hardware accelerators via a high-speed network interconnect, and overall performance and throughput may be improved.

This invention discloses a general cognitive enhancement platform, system, method, and storage medium. The method includes: maintaining a scene registry, which stores the definition of at least one cognitive enhancement scene. Each scene definition includes a scene identifier, functional modules, a processing engine, and a pipeline mode; responding to requests to activate a specific cognitive enhancement scene; loading the corresponding functional modules and processing engine according to the scene definition in the scene registry and configuring the pipeline mode; processing input data through the processing engine to generate enhanced content via the functional modules; and presenting the enhanced content to the user. This invention also provides independent vision correction methods and systems, and real-time translation methods and systems. This invention achieves a scalable architecture for cognitive enhancement applications through a scene registry, solving the technical problems of closed architecture, lack of scalability, and repetitive functional development in existing technologies.

Disclosed is an electromagnetic-circuit co-design approach for massively reconfigurable, multifunctional, and high-speed programmable metasurfaces with integrated chip tiling. The ability to manipulate the incident electromagnetic fields in a dynamically programmable manner and at high speeds using integrated chip tiling approach is also disclosed. The scalable architecture uses electromagnetic-circuit co-design of metasurfaces where each individual subwavelength meta-element is uniquely addressable and programmable. The disclosed device comprises a large array of such meta-elements. The design relies on integrated high frequency switches designed in conjugation with meta-element for massive reconfigurability of incident amplitude and phase. The disclosed chip is multi-functional and can perform beamforming, high speed spatial light modulation, dynamic holographic projections, and wavefront manipulation.

The application provides an Internet of Things edge computing gateway system and method with an extensible architecture, and belongs to the technical field of Internet of Things applications. The gateway system comprises a hardware system and a software system. The hardware system supports multiple types of protocols and device access in physical connection. The software system adopts a micro-service architecture based on containers, and comprises a network access layer, a device abstraction layer, a custom logic layer and a cloud connection layer, four-layer systems, to provide multiple functional components such as device connection services, configuration management services, edge computing services and data uploading services. The gateway has wide applicability and can be applied to various application scenarios such as intelligent factories, smart homes and smart agriculture. The gateway has strong extensibility in terms of software and hardware functions, meets the flexible customization requirements of edge computing applications, has high reliability and security, and provides a user-friendly configuration management interface.

Embodiments relate to a waveform processing device. The device can include a first input node configured to receive a first signal and a second input node configured to receive a second signal. The device can include a pulse generator including a self-timed digital converter (DTC) with a clock generator (CLK). The device can include a switching network configured to be driven by an output from the pulse generator to modulate the first signal and the second signal in synchronization.

In one embodiment, an apparatus includes a first die adapted on a second die. The first die may have a plurality of cores, each of the plurality of cores associated with a first plurality of through silicon vias (TSVs), and the second die may have dynamic random access memory (DRAM). The DRAM of the second die may have a plurality of local portions, each of the plurality of local portions associated with a second plurality of TSVs, where each of at least some of the plurality of cores are directly coupled to a corresponding local portion of the DRAM by the corresponding first and second plurality of TSVs. Other embodiments are described and claimed.

A method for providing an extensible architecture to facilitate automated event management is disclosed. The method includes receiving an indication that relates to an occurrence of a first event, the indication including event data; parsing the event data to generate event messages that correspond to the first event, each of the event messages relating to a structured data set that is accessible within a network environment; applying, by using the at least one event message, a rule and a corresponding trigger to accounts that are associated with the first event; initiating resolution actions for each of the accounts based on the rule and the corresponding trigger; and modifying a resolution indicator that is associated with each of the accounts based on results of the resolution actions.

During a command bus training (CBT), interconnected memory dice are accessed in a sequence determined (e.g., predetermined) by a bit sequence generator and via a shared data link for retrieving a respective set of feedback data of the CBT from each memory dice. This eliminates a need to individually train and / or control interconnected memory dice for the CBT; thereby, providing a flexible and scalable architecture that can accommodate a range of memory densities (e.g., a number of memory dice that are interconnected) and making it a valuable solution for high-performance memory applications.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring. The framework incorporates self-healing capabilities using reinforcement learning techniques and maintains operational efficiency through intelligent resource management and workload distribution. The framework can operate autonomously while requiring minimal cloud connectivity, featuring extensible architecture through a plugin system that enables adaptation to evolving network requirements while maintaining stable operation of existing capabilities.

Disclosed are methods and systems for automated generation of content distribution images, including receiving user input corresponding to a content distribution operation. The user input may be parsed to identify keywords. Image data corresponding to the keywords may be identified. An image processing operation may be performed on the image data. A generative adversarial network may be performed on the processed image data, the execution including running a first neural network on the processed image data to generate first images corresponding to the keywords, the first images being generated based on a likelihood that each of the first images would not have been detected as generated by the first neural network. A user interface may display the first images along with second images, including images that were previously part of the content distribution operation or images designated by an entity as available for the content distribution operation.

An access to resources and data management by servers is provided. In order to provide to users a universal access point to an application, while allowing a strict control of the ownership and localization of data, a first device receives from a user a request to access a resource, and, if the user has the right to access a resources, sends to the user an identifier of a communication endpoint of a second device, among a plurality of second devices, that is able to access the resource and deliver the resource to the client.