A mobile application development device having a platform processor, a native application converter engine, and a mobile platform framework engine configured to facilitate the development and deployment of mobile applications configured to be run on different mobile operating systems from code that is developed independently and agnostic of the mobile operating system on which it will ultimately run.

A mobile application development device having a platform processor, a native application converter engine, and a mobile platform framework engine configured to facilitate the development and deployment of mobile applications configured to be run on different mobile operating systems from code that is developed independently and agnostic of the mobile operating system on which it will ultimately run.

Embodiments described herein are directed to a programming language trigger mechanism. The trigger mechanism is a small piece of code that a software developer utilizes in a computer program. The trigger mechanism enables computing operations or tasks to be performed asynchronously and in a parallel fashion. In particular, logic (e.g., operations or tasks) associated with the trigger mechanism are provided to a plurality of resources for processing in parallel. Each resource asynchronously processes the task provided thereto and asynchronously provides the result. The results are asynchronously returned as an enumeration. The enumeration enables the software developer to enumerate through the returned elements as a simple stream of results as they are calculated.

A mobile application development device having a platform processor, a native application converter engine, and a mobile platform framework engine configured to facilitate the development and deployment of mobile applications configured to be run on different mobile operating systems from code that is developed independently and agnostic of the mobile operating system on which it will ultimately run.

A high level programming language provides extensible data parallel semantics. User code specifies hardware and software resources for executing data parallel code using a compute device object and a resource view object. The user code uses the objects and semantic metadata to allow execution by new and/or updated types of compute nodes and new and/or updated types of runtime libraries. The extensible data parallel semantics allow the user code to be executed by the new and/or updated types of compute nodes and runtime libraries.

A system and method of parallelizing programs employs runtime instructions to identify data accessed by program portions and to assign those program portions to particular processors based on potential overlap between the access data. Data dependence between different program portions may be identified and used to look for pending “predicate” program portions that could create data dependencies and to postpone program portions that may be dependent while permitting parallel execution of other program portions.

The present disclosure relates generally to the field of automatic conversion of sequential array-based programs to parallel MapReduce programs. In various examples, automatic conversion of sequential array-based programs to parallel MapReduce programs may be implemented in the form of systems, methods and/or algorithms.

Embodiments of the apparatus of dynamically renumbering ports relate to a network chip that minimizes the total logic on the network chip by limiting the number of states that needs to be preserved for all ports on the network chip. Each pipe on the network chip implements a dynamic port renumbering scheme that dynamically assigns a relative port number for each port assigned to that pipe. The dynamic port renumbering scheme allows for internal parallelism without increasing the total amount of state space required for the ports on the network chip.

A system and method for creating a concurrent programming language by extending existing programming languages. The system and method may be useful for extending known concurrent programming languages, such as Java and C#. The system and method provides a compilation process that aids concurrent programming that aids concurrent programming by extending existing programming languages. The extended languages will support signals, concurrent objects, and concurrent expressions. The system and method does not use contracts or futures, but rather uses a different type of object that is understood with a different type of concurrent expression. In one embodiment, an asynchronous object is used.

A method and an apparatus that execute a parallel computing program in a programming language for a parallel computing architecture are described. The parallel computing program is stored in memory in a system with parallel processors. The system includes a host processor, a graphics processing unit (GPU) coupled to the host processor and a memory coupled to at least one of the host processor and the GPU. The parallel computing program is stored in the memory to allocate threads between the host processor and the GPU. The programming language includes an API to allow an application to make calls using the API to allocate execution of the threads between the host processor and the GPU. The programming language includes host function data tokens for host functions performed in the host processor and kernel function data tokens for compute kernel functions performed in one or more compute processors, e.g. GPUs or CPUs, separate from the host processor. Standard data tokens in the programming language schedule a plurality of threads for execution on a plurality of processors, such as CPUs or GPUs in parallel. Extended data tokens in the programming language implement executables for the plurality of threads according to the schedules from the standard data tokens.