A system includes persistent storage configured to store definitions of interfaces of remote software applications, and a software application configured to define the interfaces. The software application identifies a remote software application system by which the remote software applications are exposed for execution, and obtains therefrom a specification of a particular remote software application. The software application determines, based on the specification, (i) objects accessible by way of the particular remote software application and (ii) functions invokable to interact with the objects. The software application generates actions that define an interface for the particular remote software application. Each action is configured to invoke execution of one or more of the functions by transmitting a request to the remote software application system and, in response, receive, by way of the remote software application system, an output of the one or more of the functions. The actions are stored in the persistent storage to define the interface.

One embodiment includes acceleration systems that operate as intermediaries between the API processing system and the clients to reduce API call roundtrip latencies. The acceleration systems are a network of interconnected systems that are distributed across the globe. A given acceleration system establishes a network connection with a given client and receives a request for processing an API call over the connection. The programming function associated with the API call is configured in the API processing system. The acceleration system facilitates the processing of the API call over an established connection with the API processing system.

A method includes detecting, by a computing device, activation of a link to content served by a remote server, and in response to detecting activation of the link, attempting to load a passive mixed content item from the computing device. The method also includes determining whether the passive mixed content item successfully loaded. The method further includes, in response to determining the passive mixed content item successfully loaded, accessing, using an application on the computing device, the content from the remote server. In addition, the method includes, in response to determining the passive mixed content item did not successfully load, accessing, using a web browser, the content from the remote server.

Systems and methods are disclosed that enable distributed execution of prediction models by disparate, remote systems. Prediction model code is transmitted to the disparate, distributed systems for execution by the disparate, remote systems. Default model input data may be independently modified by a given system, and the modified input data may be used when the given system executes the model. Model predictions and associated model parameters are received from the disparate, distributed systems. The accuracy of the received model predictions from the disparate, distributed systems are analyzed. Based on the analyzed accuracy of the received model predictions, a determination is made as to which model predictions satisfy at least a first criterion. Computer-based resources are allocated using the determination as to which model predictions satisfy at least the first criterion.

An information handling system operating as a thin client across a 5G infrastructure may include a wireless network interface device to communicate with a 5G communication network using a mm-wave antenna transceiver; an input/output (I/O) controller to send user input across to the 5G communication network to a backend server via a 5G antenna transceiver; and a graphical processing unit (GPU) to: transmit graphics data across the 5G communication network; and receive application program interface (API)-processed graphics data across the 5G communication network from the backend server descriptive of a user interface to be displayed on a video display communicatively coupled to the GPU.

A method, system, and computer-readable storage medium for creating and executing containerized applications in cloud computing are disclosed. For example, one method involves identifying a command. Such a command indicates an application to be executed by a compute node. The method also involves generating a job for transmission to the compute node. The job indicates a container. The compute node, upon receipt of the job, is configured to create an environment for such a container, execute the application within the container, and generate results of the execution of the application.

Techniques are disclosed that can obtain a description of intended digital content data in a producer computer, create a task graph of the intended digital content data, send the task graph to a consumer computer over a bus, execute the task graph locally in the consumer computer to realize an approximation of the intended digital content data, and render the approximation of the intended digital content data on a local display or other appropriate output device.

A method, system, and computer-readable storage medium for creating and executing containerized applications in cloud computing are disclosed. For example, one method involves identifying a command. Such a command indicates an application to be executed by a compute node. The method also involves generating a job for transmission to the compute node. The job indicates a container. The compute node, upon receipt of the job, is configured to create an environment for such a container, execute the application within the container, and generate results of the execution of the application.

Embodiments as disclosed herein provide for methods and systems that give firmware in a given node the ability to control the hardware configuration and activity of every endpoint in every remote node within the array. The standard, inter-node, message passing interconnect and protocol are utilized for this purpose.

A method for executing a task by a scheduling device, belonging to the technical field of electronics. The method includes: acquiring a target algorithm corresponding to a target task to be executed; acquiring an execution environment condition for a target algorithm, and current execution environment information of various execution devices; in the execution devices, determining a target execution device of which the execution environment information satisfies the execution environment condition; and sending a control message for executing the target task to the target execution device.