Abstract: The disclosed technology is generally directed to virtualization technology. The disclosed technology includes providing processor feature ID information requested by, or from, a virtual machine (VM), virtualized application, Virtualization Based Security (VBS) user mode process, VBS kernel mode process, or other guest partition, by a processor. Such information may be provided based on information provided a priori to the processor, for example, by a supervisory partition, such as a hypervisor. The disclosed technology also includes a supervisory partition, for example, that provides such information to the processor, and includes guest partitions that receive such information.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for efficiently processing data to allow for the streamlined assessment of risk ratings for one or more vendors. In various embodiments, the systems/methods may use one or more particular vendor attributes (e.g., as determined from scanning one or more webpages associated with the particular vendor) and the contents of one or more completed privacy templates for the vendor to determine a vendor risk rating for the particular vendor. As a particular example, the system may scan a website associated with the vendor to automatically determine one or more security certifications associated with the vendor and use that information, along with information from a completed privacy template for the vendor, to calculate a vendor risk rating that indicates the risk of doing business with the vendor.

Abstract: An on-board update device and an on-board update system provided herein may prevent a decrease in the electric power charged in the battery caused by an update. An on-board update device has an update processing unit configured to update a program stored in a storage unit of a communication device. The on-board update device includes: an update information acquisition unit; a required electric power estimation unit; and a battery level acquisition unit acquires an amount of electric power charged in the battery. The update processing unit performs an update process in consideration of the amount of electric power estimated by the required electric power estimation unit, the amount of electric power acquired by the battery level acquisition unit, and a priority level of the update program or data acquired by the update information acquisition unit.

Abstract: Examples described herein include systems and methods for synchronizing applications that target different software development kits (“SDK”). The system can execute a bridge application that registers an implementation of a content provider class. This allows the bridge application to communicate with a first application targeting a first SDK. The bridge application can also register to send and receive implicit broadcasts. After the bridge application verifies the request, it can broadcast to a second cluster of applications registered with an operating system to receive implicit broadcasts. Similarly, the bridge application can receive implicit broadcasts and synchronize those requests with a first cluster of applications by using the implemented content provider methods.

Abstract: Computational apparatus including multiple processing cores, which concurrently execute tasks that are respectively assigned to them. A central scheduling unit (CSU) including a CSU memory holding one or more look-up tables (LUTs) listing tasks for allocation to the processing cores and respective conditions for enabling of each of the tasks. The CSU receives indications of termination of the tasks by the processing cores, and selects, responsively to the indications, enabled tasks from the one or more LUTs for allocation to the processing cores. A network of distribution units are connected between the CSU and the processing cores. The distribution units allocate selected tasks from the CSU to the processing cores for execution and report the termination of the tasks from the processing cores to the CSU.

Abstract: Disclosed are examples related to building a customized data collection widget. Building of the customized data collection widget includes receiving a selection of several universal modules for inclusion in the widget. Each universal module of the selected several universal modules may include programming code that causes rendering of user-fillable data fields on a display, and a summary page including data requirements of the respective universal module. Based on the data requirements in a summary page of each respective universal module of the selected several universal modules, the selected several universal modules retrieved from a module repository may be combined in a customized data collection container stored in a composite repository. The selected customized data collection container may be combined with selected other data collection containers to form a uniquely identifiable, customized data collection widget. The customized data collection widget may be delivered to the composite repository.

Abstract: Systems and methods are described for simulated data object storage on a data storage system. The system may allow clients to store computed data objects, which are generated from a source data object based on a user-defined transformation. For example, computed data objects may be thumbnail images generated based on a full resolution image. When a request to store a computed data object is received, the system can predict a timing of a next request for the data object. If expected resource consumption associated with storing the data object until a next request exceeds expected resource consumption associated with generating the data object in response to the next request, the system can acknowledge the request to store the data object, but not actually store the data object. Instead, the system may generate the data object in response to the next request.

Abstract: A container deployment method increases access speed between isolated containers on a same host. The method includes: receiving a container deployment message including container image information and association information of a container; creating a container for a first service, and a first network namespace and a first IPC namespace corresponding to the container for the first service; creating a first load balancing container corresponding to the container for the first service, and setting a running parameter of the first load balancing container to a parameter of the first network namespace; creating a loopback interface in the first network namespace; determining that the network device has a container that is for a second service and that is associated with the container for the first service; and setting a starting parameter of the first load balancing container to a parameter of a second IPC namespace.

Abstract: Disclosed embodiments relate to generating an update package for updating software on an Electronic Control Unit (ECU) in a vehicle. Operations may include accessing a plurality of attributes of a software update to be stored on the ECU in the vehicle; accessing a corresponding plurality of attributes of current software stored on the ECU in the vehicle; comparing the plurality of attributes with the corresponding plurality of attributes; generating a delta file representing differences between the plurality of attributes and the corresponding plurality of attributes determined in the comparison; and providing the delta file to the ECU, wherein the delta file is configured to be processed by startup code in the ECU that enables the delta file to execute in the ECU in the vehicle.

Abstract: A method is provided for consistent data processing by first and second distributed processing systems having different data partitioning and routing mechanisms such that the first system is without states and the second system is with states. The method includes dividing data in each system into a same number of partitions based on a same key and a same hash function. The method includes mapping partitions between the systems in a one-to-one mapping. The mapping step includes calculating a partition ID based on the hash function and a total number of partitions, and dynamically mapping a partition in the first system to a partition in the second system, responsive to the partition in the first system being unmapped to the partition in the second system.

Abstract: A computer implemented method includes executing a user space partition first real-time task from a real-time task queue on a real-time kernel thread executing on a computing core of a computer, wherein the real-time kernel thread is scheduled by an operating system scheduler, pre-empting the first real-time task via a user space partition real-time task scheduler in response to a task switch signal, saving a first real-time task context, loading a user space second real-time task context for use by the real-time kernel thread via the user space partition real-time task scheduler, and executing the second real-time task from the real-time task queue on the real-time kernel thread.

Abstract: The disclosed technology is generally directed to virtual machines. In one example of the technology, data associated with a virtual machine configuration request is received. A first virtual machine to be reconfigured is provided. The first virtual machine is booted. The first virtual machine is a system virtual machine, the first virtual machine is re-provisioned into be reconfigured in accordance with the virtual machine configuration request without rebooting the first virtual machine.

Abstract: Technologies for scheduling workload submissions for a graphics processing unit (GPU) in a virtualization environment include a GPU scheduler embodied in a computing device. The virtualization environment includes a number of different virtual machines that are configured with a native graphics driver. The GPU scheduler receives GPU commands from the different virtual machines, dynamically selects a scheduling policy, and schedules the GPU commands for processing by the GPU.

Abstract: Embodiments of the present disclosure provide a method, device and computer-readable storage medium for managing virtual machines. In accordance with embodiments of the present disclosure, tags in a virtual machine system are selected based on condition information input by a user. The virtual machines are retrieved for the selected tags. In this way, less data is required to be transmitted over the network and less data is required to be processed in order to retrieve specific virtual machines.

Abstract: A present invention embodiment manages resources of a distributed system to perform computational tasks within a specified time interval. A received object is classified into a type of computational processing, and a quantity of objects is maintained for each type. An execution time for processing a single object is estimated based on a corresponding computation resource template. A total execution time for the quantity of objects of a type of computational processing is determined based on the estimated execution time. In response to the total execution time exceeding a user-specified time interval, an amount of resources of the distributed system is determined to process the quantity of objects of the type within the user-specified time interval. Nodes of the distributed system with objects classified in the type use the determined amount of resources to process the quantity of objects for the type within the user-specified time interval.

Abstract: Software, firmware, and systems repurpose existing virtual machines. After a virtual machine is created, the system stores data associated with the virtual machine to permit its later repurposing. Repurposing data includes data associated with the virtual machine when the virtual machine is in a generic state from which it may be configured for use by two or more users/applications. When the system receives a request to create a new virtual machine, rather than create a brand new virtual machine, the system repurposes an existing virtual machine. The system identifies a virtual machine to repurpose, deletes data associated with the identified virtual machine, and loads a saved copy of repurposing data. The system may then load user data or otherwise customize the database and virtual machine.

Abstract: A multi-processor system includes a plurality of processors, a scheduler, and a selector. Each of the plurality of processors is included in at least one of a plurality of domains. The plurality of domains include three or more domains and are defined based on a hierarchical domain structure. The scheduler receives and manages at least one task performed by the plurality of processors. The selector selects one of the plurality of domains based on states of the plurality of domains to assign the at least one task to the selected domain, and selects at least one processor among processors in the selected domain based on states of the processors in the selected domain to assign the at least one task to the selected processor, when the at least one task is received.

Abstract: A task allocation system for dynamically allocating computing tasks to networked computing resources with heterogeneous capabilities includes: a task library having a plurality of tasks, each task being one of a plurality of different implementations of an application, wherein the different implementations of an application provide different levels of accuracy and resource usage during execution, wherein the different implementations are configured based on a trade-off between level of accuracy and resource usage during execution; and a real-time scheduler module configured to monitor available computing resources and connectivity to the computing resources, receive a plurality of task requests, prioritize applications to be executed when performing the tasks wherein more critical applications are assigned a higher priority, allocate computing resources to the higher priority applications, allocate remaining computing resources to other applications, and select specific implementations of applications for ass

Abstract: In an embodiment, a processing device receives an instruction to schedule an event associated with a remote target device, generates a schedule for the remote target device, and transmits the schedule to the remote target device. The processing device receives usage information from the remote target device and additional usage information from other remote devices. The processing device applies a machine learning algorithm to the usage information and the additional usage information to determine an update to the schedule. The processing device updates the schedule and sends the update to the remote target device.

Abstract: A controller includes one or more hardware components for performing operations, an interconnect, and a plurality of processors connected to the one or more hardware components through the interconnect. Each processor of the plurality of processors is configured to perform multithreading to concurrently handle multiple threads of execution, and assign a different thread identifier or master ID value to each concurrently handled thread of execution. An instruction is generated for a hardware component by executing a thread of the concurrently handled threads of execution. The instruction includes the thread identifier or indicates the master ID value assigned to the thread. The generated instruction is sent to the hardware component through the interconnect.