Disclosed are mechanisms for sharing content through content consumption systems. A sharing module publishes content in a share and metadata associated therewith to a content consumption system external to a managed repository. The share represents a folder or directory in the managed repository. The publication can be made through application programming interface (API) calls handled by a first sharing module API, a repository API, a second sharing module API, and a content consumption system API. These APIs together provide a one-to-one mapping of communications protocols used by the managed repository and the external system. The share in the managed repository and the share published to the content consumption system are synced and any conflict between the two is detected and resolved. The shared content can be repatriated back to the managed repository and the shared version deleted from the content consumption system.

The invention relates to a work machine and a method for monitoring a control system at a work machine (1a). According to the method, in-parameters (32, 34, 36, 38) are obtained in the form of signals from the control system, wherein the control system generates actual values on one or more out-parameters (42, 44) in the form of signals based on said in-parameters. A characteristic of the invention is that a digital flow of data, comprising both said in-parameters and out-parameters via a control bus (5a, 5b), is addressed to a RAM buffer memory (3b,3c), which is included in a personal computer (3a) onboard the work machine, which buffer memory in FIFO mode writes a data file (id:1.1-id1:n) of a predetermined size, which is saved in a non-volatile data support memory (3d).

A learning device includes a data storage unit configured to store learning data for learning a decision tree; a learning unit configured to determine whether to cause learning data stored in the data storage unit to branch to one node or to the other node of lower nodes of a node based on a branch condition for the node of the decision tree; and a first buffer unit and a second buffer unit configured to buffer learning data determined to branch to the one node and the other node, respectively, by the learning unit up to capacity determined in advance. The first buffer unit and the second buffer unit are configured to, in response to buffering learning data up to the capacity determined in advance, write the learning data into continuous addresses of the data storage unit for each predetermined block.

Various embodiments of the present application set forth a computer-implemented method for accessing data comprising identifying a first set of read operations occurring during a first time period, where each read operation included in the set of read operations is associated with retrieving a different portion of at least one object from a storage system, determining a byte density associated with the set of read operations, where the byte density indicates a size of contiguous portions of the at least one object that were retrieved during the first time period, and determining, based on the byte density, a pre-buffering block size for a read operation during a second period, where the pre-buffering block size specifies a size of a portion of at least one object that is to be retrieved from the storage system.

Representative apparatus, method, and system embodiments are disclosed for configurable computing. A representative system includes an interconnection network; a processor; and a plurality of configurable circuit clusters. Each configurable circuit cluster includes a plurality of configurable circuits arranged in an array; a synchronous network coupled to each configurable circuit of the array; and an asynchronous packet network coupled to each configurable circuit of the array. A representative configurable circuit includes a configurable computation circuit and a configuration memory having a first, instruction memory storing a plurality of data path configuration instructions to configure a data path of the configurable computation circuit; and a second, instruction and instruction index memory storing a plurality of spoke instructions and data path configuration instruction indices for selection of a master synchronous input, a current data path configuration instruction, and a next data path configuration instruction for a next configurable computation circuit.

Examples are disclosed that relate to processing files between a local network and a cloud computing service. One example provides a computing device configured to be located between a local network and a cloud computing service, comprising a logic machine and a storage machine comprising instructions executable to receive, from a device within the local network, a file at a local share of the computing device, and in response to receiving the file, generate a file event indicating receipt of the file at the local share and provide the file event to a virtual machine executing on the computing device. The instructions are further executable to, based upon a property of the file, provide the file to a program operating within a container in the virtual machine to process the file, and send a result of executing the program on the file to the cloud computing service.

An application includes main program code, but also a call handler and an update module. When a specific method or function in the operating system is called, the call is redirected to the call handler in the application. The call handler then calls the function in the operating system. The function retrieves an object to present in a user interface to the application. But before the object is rendered, program control is returned to the call handler, which calls into the update module. The update module determines whether or not the appearance of the object should be changed, for example, in accordance with an A/B test or any other type of update. If so, visual characteristics of the object are changed. Control reverts back to the operating system from the call handler and the object, in its changed form, is presented in the user interface.

A universal floating-point Instruction Set Architecture (ISA) compute engine implemented entirely in hardware. The ISA compute engine computes directly with human-readable decimal character sequence floating-point representation operands without first having to explicitly perform a conversion-to-binary-format process in software. A fully pipelined convertToBinaryFromDecimalCharacter hardware operator logic circuit converts one or more human-readable decimal character sequence floating-point representations to IEEE 754-2008 binary floating-point representations every clock cycle. Following computations by at least one hardware floating-point operator, a convertToDecimalCharacterFromBinary hardware conversion circuit converts the result back to a human-readable decimal character sequence floating-point representation.

A method performed by a device (e.g., touch controller) includes deriving a pen position, and transmitting a report indicating the derived pen position to a host computer. The report includes a first area storing position data indicating the derived position and a second area storing non-position data different from the position data. The method includes securing a buffer area for retaining a plurality of the reports in a memory, deriving the pen position at each determined scanning time, and generating a report including the position data indicating the derived position. The method includes storing the report in the buffer area and, in response to obtaining the non-position data, writing the non-position data in the second area of each of one or more of the reports stored in the buffer area. The method includes transmitting the plurality of the reports stored in the buffer area to the host computer.

Systems and methods are described for providing a user interface through which a user can program operation of a data processing pipeline by specifying a graph of nodes that transform data and interconnections that designate routing of data between individual nodes within the graph. In response to a user request, a preview mode can be activated that causes the data processing pipeline to retrieve data from at least one source specified by the graph, transform the data according to the nodes of the graph, sample the transformed data, and display the sampling of the transformed data to at least one node without writing the transformed data to at least one destination specified by the graph.