Abstract: A method of merging commits of code in a parallel code base environment. The method comprises receiving a plurality of tickets from a ticket data store by a commit merge application executing on a computer system, wherein each ticket comprises at least one commit comprising a commit identifier and a timestamp, extracting the at least one commit identifier from each of the plurality of tickets, and ordering the extracted commit identifiers from earliest to most recently committed based on the timestamp. Based on the ordering, the method further comprises merging the commits of the test code branch with a master code branch, identifying conflicts between the commits of the test code branch with the master code branch, and resolving any identified conflicts to a later commit.

Abstract: In some implementations, a user device can generate configuration data for an application on the user device using multilevel configuration data. For example, an application on the user device can obtain application level configuration data from a server device. The application level configuration data can be generated based on user engagement segments associated with the user of the user device, for example. The application can obtain publisher level configuration data generated by a content publisher. In response to requesting a content item, the application can receive content level configuration data. The application can combine the application level configuration data, the publisher level configuration data, and/or the content level configuration data to generate dynamic configuration data. The dynamic configuration data can be used by the application to determine, among other things, what content to present to the user of the application on the user device.

Abstract: An example method is provided for recommending VM configurations, including one or more servers upon which one or more VMs can run. A user wishing to run these VMs can request a recommendation for an appropriate server or set of servers. The user can indicate a category corresponding to the type of workload that pertains to the VMs. The system can receive the request and identify a pool of servers available to the user. Using industry specifications and benchmarks, the system can classify the available servers into multiple categories. Within those categories, similar servers can be clustered and then ranked based on their levels of optimization. The sorted results can be displayed to the user, who can select a particular server (or group of servers) and customize the deployment as needed. This process allows a user to identify and select an optimized setup quickly and accurately.

Abstract: A method for controlling a field device coupled to an automation network, in which the field device has an associated tool device selected from a group of predetermined tool devices, includes the steps of: coupling the selected tool device to a control device having a physical port device; choosing a virtual link unit from a group of virtual link units included in the control device as a function of the selected tool device, wherein each of the virtual link units corresponds to one of the predetermined tool devices; and establishing a control link between the chosen control device and the selected tool device being associated to the field device via the physical port device using control data included in the chosen virtual link unit.

Abstract: A method includes accessing a schema that specifies relationships among datasets, computations on the datasets, or transformations of the datasets, selecting a dataset from among the datasets, and identifying, from the schema, other datasets that are related to the selected dataset. Attributes of the datasets are identified, and logical data representing the identified attributes and relationships among the attributes is generated. The logical data is provided to a development environment, which provides access to portions of the logical data representing the identified attributes. A specification that specifies at least one of the identified attributes in performing an operation is received from the development environment.

Abstract: Embodiments herein describe techniques for interfacing a neural network application with a neural network accelerator that operate on two heterogeneous computing systems. For example, the neural network application may execute on a central processing unit (CPU) in a computing system while the neural network accelerator executes on a FPGA. As a result, when moving a software-hardware boundary between the two heterogeneous systems, changes may be made to both the neural network application (using software code) and to the accelerator (using RTL). The embodiments herein describe a software defined approach where shared interface code is used to express both sides of the interface between the two heterogeneous systems in a single abstraction (e.g., a software class).

Abstract: Managing composable compute system infrastructure with support for decoupled firmware updates includes mapping a device to a server, wherein the device is in a resource pool of devices including at least one idle device, and wherein the device and the server are within a pod of composable compute elements connected by a fabric in a composable system executing a workload; detecting that the device has a needed firmware update; exchanging, transparent to the workload executing in the composable system, the mapping for the device with the needed firmware update and the idle device in the resource pool; and performing the firmware update on the unmapped device as the workload executes in the composable system with the newly mapped device.

Abstract: In some examples, thermal aware optimization logic determines a characteristic (e.g., a workload or type) of a wavefront (e.g., multiple threads). For example, the characteristic indicates whether the wavefront is compute intensive, memory intensive, mixed, and/or another type of wavefront. The thermal aware optimization logic determines temperature information for one or more compute units (CUs) in one or more processing cores. The temperature information includes predictive thermal information indicating expected temperatures corresponding to the one or more CUs and historical thermal information indicating current or past thermal temperatures of at least a portion of a graphics processing unit (GPU). The logic selects the one or more compute units to process the plurality of threads based on the determined characteristic and the temperature information. The logic provides instructions to the selected subset of the plurality of CUs to execute the wavefront.

Abstract: In a method for operating a production machine or machine tool, an app having at least one virtual container and an app configuration is downloaded from a remote memory store into a memory store of the machine, and an immediate start of the downloaded app on the production machine or machine tool is automatically prevented. The app configuration of the downloaded app is then automatically modified, and identifiers included in the app configuration are automatically evaluated and compared with identifiers included in a positive list or in a positive list and a negative list. An identifier which is not contained in the positive list, or an identifier which is contained in neither the positive list nor in the negative list is automatically replaced with an automatically selected or automatically generated target expression; and the downloaded app following the modification of the app configuration is then automatically started.

Abstract: Systems and methods for intelligent data center power management and energy market disaster recovery comprised of data collection layer, infrastructure elements, application elements, power elements, virtual machine elements, analytics/automation/actions layer, analytics or predictive analytics engine, automation software, actions software, energy markets analysis layer and software and intelligent energy market analysis elements or software. Plurality of data centers employ systems and methods comprising a plurality of Tier 2 data centers that may be running applications, virtual machines and physical computer systems to enable data center and application disaster recovery from utility energy market outages.

Abstract: A control device includes a communication device configured to receive, from a control target device connected to the control device through a network, configuration information on a configuration of software and/or hardware of the control target device, a controller configured to acquire a display article from a server device connected to the control device through the network, and determine whether to store the display article in a storage as display data, based on the configuration information, and the storage configured to store the display data based on the determination by the controller.

Abstract: A graphical block diagram can be used to execute multiple operating modes, such as a code generation or simulation mode. The graphical block diagram may include at least a first graphical block used solely in a first operating mode and a second graphical block used solely in a second operating mode. Each of the first and second graphical blocks includes a respective input receiving an input from a defined mode block. The defined mode block produces a mode output indicating a selection of one of the multiple operating modes. Other blocks of the graphical block diagram may be used in more than one operating mode. Depending on the value of the mode output, the graphical block diagram is interpreted according to the first or second operating mode. More than two operating modes are possible. The techniques described herein improve a model-based development platform.

Abstract: The present disclosure relates to platform configured to recommend Visual and Execution templates to automate exploration across one or more disparate systems. The platform is configured for receiving data from a target system. Further, the platform is configured to identifying a set of best fit templates, from a set of templates. In one embodiment, the set of templates may comprise one or more templates created by the user, one or more templates published by other users associated with the user, and one or more system generated templates. The platform is configured to analyze the set of templates based on the type of data received from the target system and a set of predefined rules to identify a subset of best fit templates (discovered Templates) from the set of templates. Furthermore, the platform is configured to execute the subset of best fit templates for performing one or more data processing operations.

Abstract: Computer systems and associated methods are disclosed to implement a collaborative dataset management system (CDMS) for machine learning (ML) data. In embodiments, CDMS allows many users to create, review, and collaboratively evolve ML datasets. In embodiments, dataset owners may make their datasets available to other users on CDMS for a fee and under specified licensing conditions. CDMS users can search for other users' datasets on the system to use in their own ML tasks. CDMS users may also create child datasets from existing datasets on the system. Parent and child datasets may be linked so that changes to one dataset are provided to the other via merge requests. A dataset owner may use CDMS to review an incoming merge request using one or more audit jobs before approving the request. In this manner, CDMS provides a shared repository and collaboration system for managing high-quality datasets to power machine learning processes.

Abstract: An electronic control unit includes a first non-volatile memory configured such that a control program is written thereto; a second non-volatile memory configured such that an identifier is written thereto; and a processor. The identifier is for verifying whether the control program is correct. The processor chooses either an identifier contained in advance in the control program or an identifier written in the second non-volatile memory, depending on how and/or whether the identifier is written in the second non-volatile memory. The processor verifies whether the control program is correct based on the chosen identifier.

Abstract: A running control method includes determining a remaining running space of a first household appliance, receiving a remaining running space sent by a second household appliance connected with the first household appliance in an Internet of Things, and determining one of the second household appliance and the first household appliance having the remaining running space meeting a preset remaining running space condition as a control-side household appliance.

Abstract: Systems and methods are provided for maintaining an air conditioning system. A system can include one or more sensors positioned inside of the air conditioning system configured to transmit current sensor data to a remote location. A data repository contains historic sensor data and corresponding air conditioning system status data. A neural network is trained using the historic sensor data and the corresponding air conditioning system status data to predict a future air conditioning system status based on the transmitted current sensor data. A server computer system is configured to predict the future air conditioning system status based on the current sensor data using the neural network, and a graphical user interface is configured to display the predicted future air conditioning system status to a remote client. The current sensor data is stored in the data repository and the neural network is further trained based on the current sensor data.

Abstract: A method, apparatus and computer program for generating a test sequence of code 108 are described, the test sequence of code to be run on a target processing system 106 for use in testing the target processing system. The test sequence of code is based on one or more directed sequences of code 102, in which the one or more directed sequences of code are predetermined sequences of one or more directed instructions for testing predetermined parts of the target processing system. The method includes, for at least one of the one or more directed sequences of code, inserting randomly selected instructions at one or more insertion points in the directed sequence of code.

Abstract: Techniques release and/or allocate resources. Such techniques involve obtaining information related to low-usage-rate-resources, the information indicating resources of a set of resources in a storage system having usage rates lower than a threshold. Such techniques further involve receiving a request for resource release, the request comprising the number of resources to be released. Such techniques further involve determining, based on the number of resources to be released, the number of low-usage-rate-resources to be released. Via such techniques, not only the time and computing overheads for checking each resource that are needed in resource release may be reduced, but also the amount of data needed to be moved in resource release may be reduced.

Abstract: Methods and devices for usage profile based remote firmware upgrades for fire alarm system gateways are described herein. A method, includes creating a firmware upgrade package for a number of gateways of a number of fire alarm systems wherein each gateway has gateway operating firmware, panel connectivity firmware, and management firmware and wherein the firmware upgrade package has multiple parts, creating a firmware upgrade profile having information indicating the applicability of each of the multiple parts of the firmware upgrade package to one of the gateway operating firmware, panel connectivity firmware, and management firmware, comparing the firmware upgrade profile to a gateway profile of a particular gateway wherein the gateway profile contains information indicating usage characteristics for the gateway operating firmware, panel connectivity firmware, and management firmware, and selecting one or more of the multiple parts of the firmware upgrade package to download.