An automated improving of quality of service of a data center. Transients of a power grid fed to a power supply unit are monitored by a probe. Information on transients is provided across an interface to a server of the data center. Based on characteristics of the transients, a reliability of the data center is subjected to automated updating. A request for migration of workload requiring a higher reliability than the updated reliability can be sent to a central management. When the central management has identified another data center that can meet the required reliability, the central management migrates or relocates the workload to the another data center.

The disclosure relate to detecting performance regressions in software used to control autonomous vehicles. For instance, a simulation may be run using a first version of the software. While the simulation is running, CPU and memory usage by one or more functions of the first version of the software may be sampled. The sampled CPU and memory usage may be compared to CPU or memory usage by each of the one or more functions in a plurality of simulations each running a corresponding second version of the software. Based on the comparisons, an anomaly corresponding to a performance regression in the first version of the software relating to one of the one or more functions may be identified. In response to detecting the anomaly, the first version of the software and the one of the one or more functions may be flagged for review.

A device context of a device is identified based on device data including a current state of the device, and a user context of a user is identified based on user data including user interaction with a user interface for the device. A current task that the user is performing on the device in relation to the current state of the device is identified, and knowledge regarding how the user is performing the current task using the user interface is extracted, using an artificial intelligence technique with respect to the identified device context and the identified user context. The extracted knowledge for the identified current task is stored within a knowledge base, and can be used to adapt the user interface for another user performing the current task on the device in the current state.

Apparatus and methods may include a method for enabling customized jobs deployment in Autosys™, reviewing of execution results of the jobs in Autosys™, and querying the execution results. The method may include providing a verification of the deployment of a plurality of job scripts in a staging area. The staging area may be configured for arranging and deploying a plurality of job scripts in Autosys™. The method may include visually indicating, in a status line, whether each of the plurality of job scripts has been deployed in Autosys™ or is set to be deployed to, and executed in, Autosys™. The method may include importing selected contents of a log folder from Autosys™. The importing may use an import utility.

Provision of multiple register allocation sizes for threads is described. An example of a system includes one or more processors including a graphics processor, the graphics processor including at least a first local thread dispatcher (TDL) and multiple processing resources, each processing resource including a plurality of registers; and memory for storage of data for processing, wherein the one or more processors are to determine a register size for a first thread; identify one or more processing resources having sufficient register space for the first thread; select a processing resource of the one or more processing resources having sufficient register space to assign the first thread; select an available thread slot of the selected processing resource for the first thread; and allocate registers of the selected processing resource for the first thread.

The present disclosure relates to a method, a device, and a program product for managing multiple computing tasks on a batch basis. A method includes: identifying a task type of the multiple computing tasks in response to receiving a request to use a computing unit in a computing system to perform the multiple computing tasks; acquiring a scheduling time overhead incurred for scheduling the multiple computing tasks for execution by the computing unit; determining, based on the task type and the scheduling time overhead, a batch size for dividing the multiple computing tasks; and dividing the multiple computing tasks into at least one batch based on the batch size. A corresponding device and a corresponding computer program product are provided. With the example implementations of the present disclosure, the batch size for dividing multiple computing tasks can be dynamically determined, so that the performance of the computing system can meet user demands.

A dispatch element interfaces with a host processor and dispatches threads to one or more tiles of a hybrid threading fabric. Data structures in memory to be used by a tile may be identified by a starting address and a size, included as parameters provided by the host. The dispatch element sends a command to a memory interface to transfer the identified data to the tile that will use the data. Thus, when the tile begins processing the thread, the data is already available in local memory of the tile and does not need to be accessed from the memory controller. Data may be transferred by the dispatch element while the tile is performing operations for another thread, increasing the percentage of operations performed by the tile that are performing useful work and reducing the percentage that are merely retrieving data.

A computing device can intercept a request to launch a requested application. The request can be intercepted by a calling process executed by the computing device. The request can include information identifying the requested application. The computing device can determine that a user interaction is required before launching the requested application by consulting a set of application policies based on the information identifying the requested application. The computing device can establish that the calling process is associated with a controlling terminal provided by an operating system in response to determining that the user interaction is required. A process session group containing processes launched within a user session can be selectively associated with the controlling terminal by the operating system. The computing device can perform the user interaction using the controlling terminal in response to establishing that the calling process is associated with the controlling terminal.

A system may measure one or more metrics relating to the performance of a job for a set of occurrences of the job with respect to a data set. The measurements may be used to predict a completion time for a subsequent job or phase of the job on the data set. This prediction may be used to present a more accurate indication of a job completion status on the data set. The process may be repeated or performed separately for each client or set of data to provide an individualized progress meter or indicator. Thus, in some cases, variances in the data or computing systems may be reflected in the displayed progress of the job providing for a more accurate indication of job progress.

A frontend of a platform of a multiplatform system can be monitored for user input. Upon receiving a user input that includes particular content, a data object describing the context in which the user input was provided may be created. One or more automations may be selected from an automation database based on a similarity to the determined context. The selected automations can be automatically displayed for the user, thereby encouraging the user to leverage automations across multiple platforms without requiring the user to switch between different platforms and without requiring the user to learn or understand platform-specific automation engines.