Abstract: A high level programming language provides a read-only communication operator that prevents a computational space from being written. An indexable type with a rank and element type defines the computational space. For an input indexable type, the read-only communication operator produces an output indexable type with the same rank and element type as the input indexable type but ensures that the output indexable type may not be written. The read-only communication operator ensures that any attempt to write to the output indexable type will be detected as an error at compile time.

Abstract: A high level programming language provides an agile communication operator that generates a segmented computational space for distributing the computational space across compute nodes. The agile communication operator decomposes the computational space into segments, causes the segments to be assigned to compute nodes, and allows the user to centrally manage and automate movement of the segments between the compute nodes. The segment movement may be managed using either a full global-view representation or a local-global-view representation of the segments.

Abstract: A high level programming language provides a nested communication operator that partitions a computational space. An indexable type with a rank and element type defines the computational space. The nested communication operator partitions a specified dimension of an index indexable type into segments specified by a segmentation vector and returns an output indexable type that represents the segments. By doing so, the nested communication operator allows data parallel algorithms to operate on the segments as individual units.

Abstract: 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.

Abstract: A high level programming language provides a nested communication operator that partitions a computational space. An indexable type with a rank and element type defines the computational space. The nested communication operator partitions a specified dimension of an index indexable type into segments specified by a segmentation vector and returns an output indexable type that represents the segments. By doing so, the nested communication operator allows data parallel algorithms to operate on the segments as individual units.

Abstract: A high level programming language provides an agile communication operator that generates a segmented computational space for distributing the computational space across compute nodes. The agile communication operator decomposes the computational space into segments, causes the segments to be assigned to compute nodes, and allows the user to centrally manage and automate movement of the segments between the compute nodes. The segment movement may be managed using either a full global-view representation or a local-global-view representation of the segments.

Abstract: A high level programming language provides a read-only communication operator that prevents a computational space from being written. An indexable type with a rank and element type defines the computational space. For an input indexable type, the read-only communication operator produces an output indexable type with the same rank and element type as the input indexable type but ensures that the output indexable type may not be written. The read-only communication operator ensures that any attempt to write to the output indexable type will be detected as an error at compile time.

Abstract: A high level programming language provides a nested communication operator that partitions a computational space. An indexable type with a rank and element type defines the computational space. The nested communication operator partitions a specified dimension of an index indexable type into segments specified by a segmentation vector and returns an output indexable type that represents the segments. By doing so, the nested communication operator allows data parallel algorithms to operate on the segments as individual units.

Abstract: A high level programming language provides a tile communication operator that decomposes a computational space into sub-spaces (i.e., tiles) that may be mapped to execution structures (e.g., thread groups) of data parallel compute nodes. An indexable type with a rank and element type defines the computational space. For an input indexable type, the tile communication operator produces an output indexable type with the same rank as the input indexable type and an element type that is a tile of the input indexable type. The output indexable type provides a local view structure of the computational space that enables coalescing of global memory accesses in a data parallel compute node.

Abstract: A high level programming language provides a read-only communication operator that prevents a computational space from being written. An indexable type with a rank and element type defines the computational space. For an input indexable type, the read-only communication operator produces an output indexable type with the same rank and element type as the input indexable type but ensures that the output indexable type may not be written. The read-only communication operator ensures that any attempt to write to the output indexable type will be detected as an error at compile time.

Abstract: A high level programming language provides an agile communication operator that generates a segmented computational space based on a resource map for distributing the computational space across compute nodes. The agile communication operator decomposes the computational space into segments, causes the segments to be assigned to compute nodes, and allows the user to centrally manage and automate movement of the segments between the compute nodes. The segment movement may be managed using either a full global-view representation or a local-global-view representation of the segments.

Abstract: An interface between a resource manager and schedulers in a process executing on a computer system allows the resource manager to manage the resources of the schedulers. The resource manager communicates with the schedulers using the interface to access statistical information from the schedulers. The statistical information describes the amount of use of the resources by the schedulers. The resource manager also communicates with the schedulers to dynamically allocate and reallocate resources among the schedulers in the same or different processes or computer systems in accordance with the statistical information.

Abstract: A process in a computer system creates and uses a meta-scheduler with meta-contexts that execute on meta-virtual processors. The meta-scheduler includes a set of schedulers with scheduler-contexts that execute on virtual processors. The meta-scheduler schedules the scheduler-contexts on the meta-contexts and schedules the meta-contexts on the meta-virtual processors which execute on execution contexts associated with hardware threads.

Abstract: Methods and systems for statistically eliding fences in a work stealing algorithm are disclosed. A data structure comprising a head pointer, tail pointer, barrier pointer and an advertising flag allows for dynamic load-balancing across processing resources in computer applications.

Abstract: A scheduler in a process of a computer system schedules tasks of a task group for concurrent execution by multiple execution contexts. The scheduler provides a mechanism that allows the task group to be cancelled by an arbitrary execution context or an asynchronous error state. When a task group is cancelled, the scheduler sets a cancel indicator in each execution context that is executing tasks corresponding to the cancelled task group and performs a cancellation process on each of the execution contexts where a cancel indicator is set. The scheduler also creates local aliases to allow task groups to be used without synchronization by execution contexts that are not directly bound to the task groups.

Abstract: Local storage may be allocated for each processing resource in a process of a computer system. Each processing resource may be virtualized and may have a one-to-one or a many-to-one correspondence with with physical processors. The contents of each local storage persist across various execution contexts that are executed by a corresponding processing resource. Each local storage may be accessed without synchronization (e.g., locks) by each execution context that is executed on a corresponding processing resource. The local storages provide the ability to segment data and store and access the data without synchronization. The local storages may be used to implement lock-free techniques such as a generalized reduction where a set of values is combined through an associative operator.

Abstract: A high level programming language provides an extensible set of transformations for use on indexable types in a data parallel processing environment. A compiler for the language implements each transformation as a map from indexable types to allow each transformation to be applied to other transformations. At compile time, the compiler identifies sequences of the transformations on each indexable type in data parallel source code and generates data parallel executable code to implement the sequences as a combined operation at runtime using the transformation maps. The compiler also incorporates optimizations that are based on the sequences of transformations into the data parallel executable code.

Abstract: A scheduler in a process of a computer system detects a task with an associated execution context that has not been previously invoked by the scheduler. The scheduler executes the task on a processing resource without performing a context switch if the processing resource executed a previous task to completion. The scheduler stores the execution context originally associated with the task for later use.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: A high level programming language provides a co-map communication operator that maps an input indexable type to an output indexable type according to a function. The function maps an index space corresponding to the output indexable type to an index space corresponding to the input indexable type. By doing so, the co-map communication operator lifts a function on an index space to a function on an indexable type to allow composability with other communication operators.