Abstract: A computing apparatus, including: a hardware computing platform; and logic to operate on the hardware computing platform, configured to: receive a microservice instance registration for a microservice accelerator, wherein the registration includes a microservice that the microservice accelerator is configured to provide, and a microservice connection capability indicating an ability of the microservice instance to communicate directly with other instances of the same or a different microservice; and log the registration in a microservice registration database.

Abstract: Embodiments are disclosed for processing multi-frame tasks in a multi-threaded digital design system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving, by a first thread, a first set of inputs on a graphical user interface, determining that the first set of inputs represent a first multi-frame request, wherein a multi-frame request includes a series of inputs that produce a continuous response, generating a first multi-frame edit task, the first multi-frame edit task including a communications channel between the first thread and a second thread for caching the first set of inputs, enqueuing the first multi-frame edit task in a task queue of the second thread, processing, by the second thread, the first multi-frame edit task.

Abstract: Systems, apparatuses and methods may provide for technology that identifies telemetry data associated with an execution of a cluster of artificial intelligence (AI) operations on an accelerated backend system, wherein the telemetry data includes one or more of temperature classifier data, compute classifier data or failure data, and determines whether to send a current instance of the cluster of AI operations to the accelerated backend system or a default backend system based on the telemetry data.

Abstract: A system and method for embedding a tool into an Integrated Development Environment (IDE) is disclosed. The system includes a special application programming interface (API) that is used to embed any tool into any IDE. The API provides a way for the tool to indicate what functions are supported by the tool. These functions may include save, print, edit and others. The API also provides a mechanism for the IDE to communicate to the tool that one of the supported functions is to be executed. Finally, the API provides a mechanism for the tool to report information to the IDE as necessary.

Abstract: A method includes receiving, by a first computer from a second computer, a stateless API request message comprising update value data, a consensus token, and a user identifier. The first computer determines whether or not the consensus token matches a previously stored consensus token. If the consensus token matches the previously stored consensus token, the first computer retrieves stored value data from a value data database based on the user identifier. The first computer then updates the stored value data with the update value data. The first computer generates an API response message comprising an indication of the update. The first computer transmits, to the second computer, the API response message.

Abstract: The present invention relates to a software method for componentized enterprise applications for backend development based on Spring Boot and Java EE application server using plugins. The object of the present invention is to build back end servers and desktop applications from reusable plugins. Another object of the present invention is the benefits of a single process implementation and truly decupled parent child dependency. Moreover, the present invention is to build entire applications (deployment in application server or Spring Application) from separate and easy to maintain run time components. Finally, the percent invention is that the invention can be used by almost any development team using Java EE and Spring for back end enterprise development. Moreover, the present invention is to allow plugins to provide their services either in the same process or on a remoter server in a transparent way to their services consumers.

Abstract: A computing system includes a processing device and a memory device configured to store an Application Programming Interface (API) and computer software. The computer software has a plurality of software components configured to enable the processing device to utilize internal data for performing a plurality of functions. The API is configured to define interactions between the software components and is further configured to define access constraints with respect to the computing system. The access constraints are configured to restrict access by an end user associated with the computing system with respect to the internal data and software components. Also, the computer software is configured to adjust the access constraints of the API.

Abstract: In one example, a computer implemented method may include retrieving resource definition data corresponding to an endpoint. The resource definition data includes resource type information. Further, an API response may be obtained from the endpoint by querying the endpoint using an API call. Furthermore, the API response may be parsed and a resource model corresponding to the resource definition data may be populated using the parsed API response. The resource model may include resource information and associated metric information correspond to a resource type in the resource type information. Further, a resource and/or metric data associated with the resource may be determined using the populated resource model. The resource may be associated with an application being executed in the endpoint.

Abstract: A method for performance tuning in Automated Machine Learning (Auto ML) includes obtaining preset application program interface and system resources of the automatic machine learning system. Performance index measurement values are obtained according to the preset application program interface when the system pre-trains deep learning training model candidates. A distribution strategy and a resource allocation strategy are determined according to the performance index measurement values and the system resources and computing resources of the system are allocated according to the distribution strategy and the resource allocation strategy. The disclosure also provides an electronic device and a non-transitory storage medium.

Abstract: One example method includes receiving, from a microservice, a service request that identifies a service needed by the microservice, and an API of an endpoint that provides the service, evaluating the service request to determine whether the service request conforms to a policy, when the service request has been determined to conform with the policy, evaluating the endpoint to determine if endpoint performance meets established guidelines, and when it is determined that the endpoint performance does not meet the established guidelines, identifying an alternative endpoint that meets the established guidelines and that provides the requested service. Next, the method includes transforming the API of the service identified in the service request to an alternative API of the service provided by the alternative endpoint, and sending the service request and the alternative API to the alternative endpoint.

Abstract: In one example, a computer implemented method may include retrieving resource definition data corresponding to an endpoint. The resource definition data includes adapter information and resource type information. Further, an adapter instance may be generated using the adapter information to establish communication with the endpoint. Furthermore, an API response may be obtained, via the adapter instance, from the endpoint by querying the endpoint using an API call. Further, the API response may be parsed. Further, a resource model corresponding to the resource definition data may be populated using the parsed API response. The resource model may include resource information and associated metric information corresponding to a resource type in the resource type information. Furthermore, a resource and/or metric data associated with the resource may be determined using the populated resource model. The resource may be associated with an application being executed in the endpoint.

Abstract: The described technology relates to a publish-subscribe message framework in which an application, decomposed to a plurality of processing stages, is run by executing respective processing stages of the application asynchronously and simultaneously with each other. Communications between the respective processing stages may exclusively be in accordance with the publish-subscribe execution model. The described publish-sub scribe framework provides for processing stages to be executed in a multi-process and/or multi-threaded manner while also enabling the distribution of the processing stages to respective processing resources in a multi-processor/multi-core processing environment. An example electronic exchange application and a corresponding example exchange gateway application are described.

Abstract: An apparatus for providing anonymity in geographic data for probe devices in a geographic region for a location-based service includes at least a database, a clustering calculator and an anonymity controller. The database stores trajectory data based on sequences of sensor measurements of the probe devices. The clustering calculator clusters the trajectory data, according to a first iteration threshold, into clusters each defined by a cluster point and compares distance for a first cluster from the clusters to cluster points of other clusters of the clusters. The clustering calculator selects a second cluster from the clusters based on the comparison of distances and merges the first cluster and the second cluster into a merged cluster. The anonymity controller modifies the trajectory data to provide a predetermined level of anonymity to locations from the trajectory data in response to the merged cluster.

Abstract: A memory system having a plurality of memory components and a controller, operatively coupled to the plurality of memory components to: store data in the memory components; communicate with a host system via a bus; service the data to the host system via communications over the bus; communicate with a processing device that is separate from the host system using a message passing interface over the bus; and provide data access to the processing device through communications made using the message passing interface over the bus.

Abstract: A data management platform for managing interconnected data and its derivatives is disclosed. For one example of the present disclosure, the data management platform receives data assets to a data management platform through an API gateway. The data assets are reformatted based upon a corresponding data model. A set of data management features are accessed through a corresponding API. The set of data management modules includes tagging, ownership, relationship, cataloging, discovery, lineage and provenance, and lifecycle. The management modules provide dynamic identification of interconnections between the data assets. Interconnections for the data assets are generated and the data assets and the interconnection data are stored based upon a format of the data.

Abstract: Techniques for intelligent compute resource selection and utilization for machine learning training jobs are described. At least a portion of a machine learning (ML) training job is executed a plurality of times using a plurality of different resource configurations, where each of the plurality of resource configurations includes at least a different type or amount of compute instances. A performance metric is measured for each of the plurality of the executions, and can be used along with a desired performance characteristic to generate a recommended resource configuration for the ML training job. The ML training job is executed using the recommended resource configuration.

Abstract: A first application programming interface (API) with a first schema may be adapted to work with a second API with a second schema using mappings of schema properties and a directed graph. An API call specification of the first API may receive first API schema properties as input and provide first API schema properties as outputs. The first API schema properties may be mapped to corresponding second API schema properties, such as using semantic representations of the schema properties. An implementation of an API call for the first API may be created by using the schema mappings and selecting a path from a directed graph corresponding to the second API, where the path includes a node corresponding to an API call of the second API. Computer code may be generated using nodes of the path, and the computer code may be stored for later use.

Abstract: In an embodiment, agricultural intelligence computer system stores a digital model of nutrient content in soil which includes a plurality of values and expressions that define transformations of or relationships between the values and produce estimates of nutrient content values in soil. The agricultural intelligence computer receives nutrient content measurement values for a particular field at a particular time. The agricultural intelligence computer system uses the digital model of nutrient content to compute a nutrient content value for the particular field at the particular time. The agricultural intelligence computer system identifies a modeling uncertainty corresponding to the computed nutrient content value and a measurement uncertainty corresponding to the received measurement values. Based on the identified uncertainties, the modeled nutrient content value, and the received measurement values, the agricultural intelligence computer system computes an assimilated nutrient content value.

Abstract: In a method for dynamically binding data in an application, an expression describing a relation between a first property of a first data of the application to a first property of a second data of the application is received. A binding is created between the first data and the second data based on the relation. A change is propagated to the first property of the second data based on a change to the first property of the first data. The receiving the expression and the creating the binding are repeated to create a plurality of bindings based on a plurality of expressions, and the receiving the expression and the creating the binding occur dynamically during an execution of the application.

Abstract: Systems and methods for determining the impact of a modification made to an API is provided. The system may include an association rule learning subsystem and a recommender subsystem. The association rule learning subsystem may receive input from an API, a metadata processor and a plurality of production logs. The API may include a plurality of API elements. The association rule learning subsystem may link each API element with one or more data elements retrieved by the metadata processors based on data retrieved from the plurality of production logs. The association rule learning subsystem may create and output a tree of API elements and linked data elements. A recommender subsystem may receive the tree. The recommender subsystem may prioritize the data elements included in the tree based on data element severity, data element frequency and data element complexity. The recommender subsystem may select a prioritized subset of the data elements.