Abstract: Methods and apparatus for using description information about a function to translate a call to the function into a call to a corresponding function in a second language. The methods include processing a definition of a function associated with a first language to create description information sufficient to enable translation of a call to the function into a call to a corresponding function in a second language without requiring processing of the definition of the function. In another aspect, the methods include providing a description file of items, each item including description information about a function associated with a first language, and using the file of description items to translate a first program file from the first language into a second language.

Abstract: A computing device-implemented method includes initiating a single programming language, and identifying, via the single programming language, one or more data distribution schemes for executing a program. The method also includes transforming, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocating the parallel program to two or more labs for parallel execution. The method further includes receiving one or more results associated with the parallel execution of the parallel program from the two or more labs, and providing the one or more results to the program.

Abstract: A device for performing parallel processing includes a processor to initiate a single programming language, and identify, via the single programming language, one or more data distribution schemes for executing a program. The processor also transforms, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocates the parallel program to two or more labs for parallel execution. The processor further receives one or more results associated with the parallel execution of the parallel program from the two or more labs, and provides the one or more results to the program.

Abstract: A device, for performing parallel processing, includes a processor to receive one or more portions of an inner context of a program created for a technical computing environment, and allocate one or more portions of the inner context of the program to two or more labs for parallel execution. The processor is also configured to receive one or more results associated with the parallel execution of the one or more portions from the two or more labs, and provide the one or more results to an outer context of the program.

Abstract: A computing device-implemented method includes receiving a program, analyzing and transforming the program, determining an inner context and an outer context of the program based on the analysis of the program, and allocating one or more portions of the inner context of the program to two or more labs for parallel execution. The method also includes receiving one or more results associated with the parallel execution of the one or more portions from the two or more labs, and providing the one or more results to the outer context of the program.

Abstract: A system, computer-readable medium, and method includes providing a control flow graph including at least one condition. An update control flow graph is automatically generated based on the provided control flow graph, where execution of the update control flow graph includes an evaluation of the condition. The update control flow graph and a value corresponding to the evaluated condition is stored. An output control flow graph based on the provided control flow graph is automatically generated, where execution of the output control flow graph is based on the stored value corresponding to the evaluated condition. A mode transition control flow graph configured to identify mode transitions for the control flow graph at one or more time intervals is automatically generated and the update control flow graph is re-executed based on the generated mode transition control flow graph.

Abstract: One or more computer-readable media store executable instructions that, when executed by processing logic, perform parallel processing. The media store one or more instructions for initiating a single programming language, and identifying, via the single programming language, one or more data distribution schemes for executing a program. The media also store one or more instructions for transforming, via the single programming language, the program into a parallel program with an optimum data distribution scheme selected from the one or more identified data distribution schemes, and allocating the parallel program to two or more labs for parallel execution. The media further store one or more instructions for receiving one or more results associated with the parallel execution of the parallel program from the two or more labs, and providing the one or more results to the program.

Abstract: In an embodiment, one or more computer-readable media holding executable instructions is provided. The instructions may be executed on a processing device to project a specification to a platform environment that includes a system model. The media may hold one or more instructions for accessing an algorithm model, the algorithm model being associated with the specification. The media may further hold one or more instructions for projecting the specification to the system model via a forward projection. The media may hold one or more instructions for receiving a reverse projection that includes specification changes, the specification changes identifying suggested changes to the specification. The media may further hold one or more instructions for modifying the algorithm model based on the specification changes, and the media may hold one or more instructions for storing the modified algorithm model.

Abstract: A system is provided that can include storage logic to store a data structure that includes an identifier. The storage logic may also store an object associated with the identifier, where the identifier may include a value, unit information, or a context. The storage logic may further store a result. The system may include processing logic to process an expression to determine whether the identifier is compatible with the expression, the determining performed using the value, the unit information, or the context. The processing logic may insert the identifier into the expression when the identifier is compatible with the expression, the inserting based on a user action. The processing logic may execute the expression on behalf of a life sciences model, may generate the result based on the executing, and may provide the result to the storage logic.

Abstract: Methods, systems and mediums are disclosed for aligning mass spectrometry data before the analysis of the mass spectrometry data. The mass spectrometry data may be received from a mass spectrometry machine, and re-sampled using a smooth warping function. To estimate the warping function, a synthetic signal is build using, for example, Gaussian pulses centered at a set of reference peaks. The reference peaks may be designated by users or calculated after observing a group of spectrograms. The synthetic signal is shifted and scaled so that the cross-correlation between the mass spectrometry data and the synthetic signal reaches its maximum value.

Abstract: A distributed graphical presentation and manipulation application executes as a thin client application in a network. The networked graphical presentation and manipulation application can generally be used without requiring a user to install any specific software prior to using the application. In one aspect, code may be received from a server, and a local environment may be generated based on the code, where the local environment may be configured to display a view of the graphical model. One or more model views to be requested may be predicted, and the predicted views may be stored in a memory for display in the local environment.

Abstract: A computing system receives a program created by a technical computing environment, analyzes the program, generates multiple program portions based on the analysis of the program, dynamically allocates the multiple program portions to multiple software units of execution for parallel programming, receives multiple results associated with the multiple program portions from the multiple software units of execution, and provides the multiple results or a single result to the program.

Abstract: A computing device-implemented method includes receiving a program created by a technical computing environment, analyzing the program, generating multiple program portions based on the analysis of the program, dynamically allocating the multiple program portions to multiple software units of execution for parallel programming, receiving multiple results associated with the multiple program portions from the multiple software units of execution, and providing the multiple results or a single result to the program.

Abstract: Exemplary embodiments may use remote processing resources to perform processing operations on behalf of a client. The embodiments may dynamically switch among available processing resources while processing is performed. Exemplary embodiments may be used, for example, to publish code, perform processing operations within a determined interval, perform scheduled processing operations, perform synchronized simultaneous execution of two or more programs, support coding competitions, support social networking and/or computing activities, and/or other types of processing activities.

Abstract: In one embodiment, a system model models characteristics of a real-world system. The system model includes a plurality of sub-portions that each correspond to a component of the real-world system. A plurality of test vectors are applied to the system model and coverage achieved by the test vectors on the sub-portions of the system model is measured. In response to a failure of the real world system, a suspected failed component of the real-world system is matched to a particular sub-portion of the system model. A test vector to be applied to the real-world system to test the suspected failed component is selected in response to coverage achieved on the particular sub-portion of the system model.

Abstract: A system and a method for implementing the system are provided. The system may include a non-Java-based application to communicate in a remote session, via a network including a plurality of remote method invocation (RMI) services, to a Java-based application using RMI; a configuration file including a reference to the non-Java based application; an RMI registry to register a set of the RMI services and the non-Java-based application using the configuration file; and an RMI activation system daemon to manage the non-Java-based application in the remote session.

Abstract: In a graphical modeling environment, a method of providing varying levels of protection relating to functionalities associated with at least some elements of a block diagram model, the method including: receiving a selection of one of the elements; receiving an indication of a desired authorization required to use at least one function of the selected element; implementing the indicated authorization for the use of the at least one function; and preventing, without obtaining of the authorization, an attempted use of the at least one function.

Abstract: A device may include a first type of modeling environment, a second type of modeling environment, and an abstract interface. The first type of modeling environment may be associated with at least one of a first toolbox or a first function. The second type of modeling environment may include a model. The second type of modeling environment may be different than the first type of modeling environment and may be incompatible with the at least one of a first toolbox or a first function. The abstract interface may interface with the first type of modeling environment and the second type of modeling environment. The abstract interface may allow the at least one of a first toolbox or a first function to be used in the model in the second type of modeling environment.

Abstract: A computer-implemented method may include defining an input bus signal in a graphical block diagram model by associating the input bus signal with a first group of signals, at least two of the first group of signals having a different data type; defining an output bus signal in the graphical block diagram model by associating the second bus signal with a second group of signals, each of the second group of signals corresponding to one of the first group of signals; defining an input to a non-virtual operation block in the graphical block diagram model as the input bus signal; defining an output to the non-virtual operation block in the graphical block diagram as the output bus signal; and simulating an operation performed on the input bus signal by the non-virtual operation block, the operation being performed on each of the first group of signals and output to each of the second group of signals.

Abstract: A computer-implemented method may include defining an input bus signal in a graphical block diagram model by associating the input bus signal with a first group of signals, at least two of the first group of signals having a different data type; defining an output bus signal in the graphical block diagram model by associating the second bus signal with a second group of signals, each of the second group of signals corresponding to one of the first group of signals; defining an input to a non-virtual operation block in the graphical block diagram model as the input bus signal; defining an output to the non-virtual operation block in the graphical block diagram as the output bus signal; and simulating an operation performed on the input bus signal by the non-virtual operation block, the operation being performed on each of the first group of signals and output to each of the second group of signals.