An application program management method and apparatus, and a non-transitory computer-readable storage medium are disclosed. The application program management method may include: determining a current extra inspection policy for a target application program according to a current running type of the target application program in response to a determination that a freezing detection of the target application program is required; determining a current inspection policy corresponding to the target application program based on a basic inspection policy corresponding to the target application program and the current extra inspection policy; and freezing the target application program in response to a determination that a running state of the target application program satisfies the current inspection policy.

A method includes receiving a request to process a set of data using a data processing application. The method includes, based on a feature associated with the set of data, selecting between (i) a first mode in which one or more running processes of the data processing application are used to process the set of data and (2) a second mode in which one or more new processes of the data processing application are started up. The method includes causing the data processing application to be executed according to the selected mode to process the set of data.

One or more example embodiments relates to a computer-implemented method for determining an optimal execution location for an application, the method comprising determining available execution locations, each of the available execution locations providing at least one execution parameter, the at least one execution parameter quantifying a suitability of the corresponding available execution location; determining the optimal execution location based on the provided execution parameters, the optimal execution location being a desired execution location for carrying out the application; and providing the optimal execution location.

The present invention relates to a method and device for validating a data flow system represented by a data flow graph, comprising: —an acquisition module (9) configured to acquire data related to first and second common parts of the data flow graph, and —a supervision module (11) configured to incrementally verify the coherence of the data flow system by verifying the local coherence of a common unidirectional connection connecting the first common part of the data flow graph to the second common part of the data flow graph at each increment.

An embodiment includes storage containing configuration and operational data related to a managed network, an action configurator application, and an action execution application. The embodiment also includes one or more processors configured to: receive, by way of the action configurator application, a specification of an action type; receive, by way of the action configurator application, a specification of an input source for actions generated using the action type; receive, by way of the action configurator application, a specification of one or more target users and an output modality for the actions; receive, by way of the action configurator application, a specification of a condition that causes the actions to be generated; determine, that the condition has been satisfied; and cause the action execution application to execute the action generator on the input source, and produce an output for one of the target users by way of the output modality.

A dataflow graph for an application has operation units that are configured to be producers and consumers of tensors. A write access pattern of a particular producer specifies an order in which the particular producer generates elements of a tensor, and a read access pattern of a corresponding consumer specifies an order in which the corresponding consumer processes the elements of the tensor. The technology disclosed detects conflicts between the producers and the corresponding consumers that have mismatches between the write access patterns and the read access patterns. A conflict occurs when the order in which the particular producer generates the elements of the tensor is different from the order in which the corresponding consumer processes the elements of the tensor. The technology disclosed resolves the conflicts by inserting buffers between the producers and the corresponding consumers.

A computation graph is accessed. In the computation graph, operations to be performed are represented as interior nodes, inputs to the operations are represented as leaf nodes, and a result of the operations is represented as a root. Selected sets of the operations are combined to form respective kernels of operations. Code is generated execute the kernels of operations. The code is executed to determine the result.

A parametric constant resolves to different values in different contexts, but a single value within a particular context. An anchor constant is a parametric constant that allows for a degree of parametricity for an API point. The context for the anchor constant is provided by a caller to the API point. The anchor constant resolves to an anchor value that records specialization decisions for the API point within the provided context. Specialization decisions may include type restrictions, memory layout, and/or memory size. The anchor value together with an unspecialized type of the API point result in a specialized type of the API point. A class object representing the specialized type is created. The class object may be accessible to the caller, but the full value of the anchor value is not accessible to the caller. The API point is executed based on the specialization decisions embodied in the anchor value.

A relevance calculation unit calculates relevance between pieces of data constituting a state chart. An individual data binarization unit binarizes the pieces of data constituting the state chart. An optimal array calculation unit calculates an array of the pieces of data constituting the state chart on the basis of the relevance calculated by the relevance calculation unit. An offset setting unit sets an offset indicating a position of each of the pieces of data binarized by the individual data binarization unit in a case where the binarized pieces of data are arranged in the array calculated by the optimal array calculation unit. A binary data integration unit integrates the pieces of data each of which has been binarized by the individual data binarization unit and for each of which the corresponding offset has been set by the offset setting unit in the array calculated by the optimal array calculation unit to obtain binary data. A state chart execution unit executes processing of the state chart on the basis of the binary data.

Control a coarse grained reconfigurable array during execution of an assembly language program identifying data flows through memory locations represented by memory variables. For example, a lowering program can be configured to receive the assembly language program, a hardware profile of the coarse grained reconfigurable array, and an instruction execution schedule to generate a configuration usable to control the coarse grained reconfigurable array. The lowering program can identify tile memories used to implement the memory locations represented by the memory variables in the assembly language program, and trace the data flows specified in the assembly language program. Using timing of instruction execution identified in the schedule, the lowering program can determine timing and controls for the dispatch interface, memory interfaces, and internal connections within tiles of the coarse grained reconfigurable array during execution of the assembly language program.