28 results about "Scalable architecture" patented technology

The system (108) in the present disclosure for service barring workflow is designed to automate and streamline the process of managing service barring actions in a telecommunications network It provides centralized control, efficient processing. and granular control over service restrictions by implementing a method (400) involving various nodes. Tracking Area Code (TAC) and Network administrators. The system (108) offers advantages such as enhanced operational efficiency. accurate enforcement of service barring rules. real-time monitoring. and reporting capabilities. It integrates with network elements and ensures compliance with regulatory requirements. With its flexible and scalable architecture, the system (108) enables administrators and users to efficiently handle service barring requests while maintaining a positive customer experience. Overall, the system (108) for service barring workflow optimizes the service management process. enhances security, and contributes to effective network control and customer satisfaction.

The invention discloses an AES encryption and decryption hardware implementation method based on an RISCV vector encryption and decryption expansion architecture, and belongs to the technical field of data encryption, and the method comprises the steps that an RISCV instruction set carries out vector expansion on AES encryption and decryption, in the AES encryption process, an initial round corresponds to a vaesz.vs instruction, a middle round corresponds to a vaesem.[ vv, vs] instruction, a final round corresponds to a vaesef.[ vv, vs] instruction, in the AES decryption process, the initial round corresponds to the vaesz.vs instruction, and in the AES decryption process, the middle round corresponds to the vaesef.[ vv, vs] instruction. The middle round corresponds to a vaesdm. [vv, vs] instruction, and the final round corresponds to a vaesdf. [vv, vs] instruction, so that the area of a chip can be reduced, the cost is reduced, the flexibility, modularization and extensible architecture design of hardware and software are enhanced, different platforms from embedded computing to high-performance computing can be easily adapted, and a solid foundation is provided for evolution and customization of a future cryptographic algorithm; and the encryption processor architecture is promoted to develop towards a more efficient, more open and more customizable direction.

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.

The invention discloses a transaction platform system of a virtual product, and the system comprises a modular transaction engine which is used for carrying out the modular splitting of a transaction process of the virtual product, and comprises a commodity management module, a user management module, a risk control management module, an order management module, a settlement management module, an after-sales management module, and a financial management module; the dynamic rule engine is used for configuring transaction parameters in real time, and the transaction parameters comprise transaction timeliness, price strategies and delivery modes; and the user growth management module is used for constructing a growth model based on the user transaction data, and converting the transaction frequency and amount of the user into a user level and a right reward. According to the invention, an integrated system architecture of a modular transaction engine, a dynamic rule engine, a growth type user system, an extensible architecture and a full-link security mechanism is constructed, so that the defects in the prior art are overcome.

Techniques and apparatuses are described for scheduling using decoupled grant and accept stages. In example aspects, an arbiter (202) of a crossbar scheduler uses buffering to decouple the grant and accept stages (314 and 318) for scheduling. The buffering divides the scheduling operation into input scheduling (310) and output scheduling (312), which can be performed in parallel. With a decoupling circuit of the arbiter (202) providing the buffering, data flows in a pipeline fashion from an initiator (302) to a target (304) across at least two cycles. The decoupling of the grant and accept stages (314 and 318) provides additional flexibility in performing the input scheduling (310) using an input-first mode (322) or an output-first mode (324). By decoupling the grant and accept stages (314 and 318), the arbiter (202) can have a scalable architecture that supports high-speed and high-throughput scheduling.

Aspects of the disclosure are directed to dynamic error correction coding (ECC) disable control. In accordance with one aspect, the disclosure includes assigning each of a plurality of control status registers (CSRs) to each of a plurality of memory groups referenced by a group index to an indicator for error correction coding (ECC) disablement; and performing a dynamic ECC disablement for a plurality of data words for writing to one of the plurality of memory groups according to the indicator in an assigned each of the plurality of CSRs.

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 special waveform generation method of an extensible framework is characterized by comprising the steps that a Visual Basic language is used for compiling a visual interface, original code element data are received, and an upper computer unpacks the original code element data into multiple pieces of subpackage data with the size being 1 KB; the first file stores the addresses of all used FLASH blocks, the second file stores the lengths of all waveforms, and the third file stores the initial address of each waveform cached to an SRAM (Static Random Access Memory); 3 files are sent to the network chip, the network chip sends data to the M FLASH for solidification and then calls the data to the N SRAMs, the FPGA calls the data from the SRAMs according to requirements and sends special waveform code elements to the DAC, and the DAC generates specific baseband waveforms and sends the baseband waveforms to the excitation source.

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.

Hardly any work in literature attempts employing Function-as-a-Service (FaaS) or serverless architecture to accelerate the training or re-training process of meta-learning architectures. Embodiments of the present disclosure provide a method and system for meta learning using distributed training on serverless architecture. The system, interchangeably referred to as MetaFaaS, is a meta-learning based scalable architecture using serverless distributed setup. Hierarchical nature of gradient based architectures is leveraged to facilitate distributed training on the serverless architecture. Further, a compute-efficient architecture, efficient Adaptive Learning of hyperparameters for Fast Adaptation (eALFA) for meta-learning is provided. The serverless architecture based training of models during meta learning enables unlimited scalability and reduction of training time by using optimal number of serverless instances. An analytical model for gradient based meta learning architectures that predicts training time required for the number of FaaS instances is provided which further enables estimating the cost incurred during training models in meta-learning.

Systems, devices, methods and architectures for quantum computing are disclosed. A system for controlling quantum elements includes input signal sources configured to generate signals, where each input signal source is coupled with at least one quantum element; and at least one controller configured to provide data signals comprising instructions, where the instructions are configured to cause the system to generate control sequences, where the sequences are configured to apply desired respective operation on the at least one quantum element, each control sequence includes a time-dependent series of control subsequences, and each control subsequence includes a signal generated by a single input signal source at a time interval, or defines a time interval during which the plurality of input signal sources does not generate signals; and apply the control sequences on the at least one quantum element.

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.

The invention provides methods, systems and computer program products for job management and for allocating resources for cloud based or remote device based job processing. The invention provides a scalable architecture for job management and for allocating resources for cloud based or remote device based job processing comprising a primary job manager machine, having a resource pool of secondary job manager machines assigned thereto. Each secondary job manager machine has a resource pool of computing machines assigned thereto—for execution jobs or computing tasks assigned to the secondary job manager machine by the primary job manager machine. In an embodiment, each secondary job manager machine has one or more accelerator cache proxies for enabling low latency data object retrieval for computing tasks being executed by the computing machines assigned to the secondary job manager.

The invention discloses a multi-mode electrical stimulation system and method based on software definition and an extensible architecture, and belongs to the technical field of medical instruments and neural engineering. The system comprises a Linux embedded master control module which runs an operating system with a real-time patch and is used for executing stimulation protocol management, digital waveform generation, data communication and system control; the high-precision digital-to-analog conversion module is connected with the main control module through a digital communication interface and is used for receiving the digital waveform instruction and generating a high-precision analog electrical stimulation signal; and the standardized extensible interface module is connected with the main control module and is used for accessing at least one external biological signal acquisition device in a plug-and-play mode. According to the invention, the flexibility, the expandability and the intelligent level of the system are greatly improved while the microsecond-level synchronization precision and the ultra-high current control precision are ensured.

Methods and systems are disclosed for automatic generation of content distribution images that include receiving user input corresponding to a content-distribution operation. The user input may be parsed to identify keywords. Image data corresponding to the keywords can be identified. Image-processing operations may be executed on the image data. Executing a generative adversarial network on the processed image data, which includes executing a first neural network on the processed-image data to generate first images that correspond to the keywords, the first images generated based on a likelihood that each image of the first images would not be detected as having been generated by the first neural network. A user interface can display the first images with second images that include images that were previously part of content-distribution operations or images that were designated by an entity as being available for content-distribution operations.

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.

To provide methods for automatic generation of content distribution images that include receiving user input corresponding to a content-distribution operation.SOLUTION: A method includes: parsing a user input to identify keywords; identifying image data corresponding to the keywords; executing image-processing operation on the image data; and executing a generative adversarial network on the processed image data, the execution including executing a first neural network on the processed-image data to generate first images that correspond to the keywords, the first images being generated based on a likelihood that each image of the first images would not be detected as having been generated by the first neural network. A user interface can display the first images with second images that include images that were previously part of content-distribution operations or images that were designated by an entity as being available for content-distribution operations.SELECTED DRAWING: Figure 4

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.